# HawkFi | Agent Terminal Deploy 24/7 quant agents for market making, liquidity providing, and Osprey-based token trading on Solana spot markets. {% hint style="info" %} Not sure where to begin? [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent), then use the [HawkFi Tutorial Library](/whitepaper/start-here/tutorials) when you want to watch the setup. {% endhint %} HawkFi is an Agent Terminal. Deploy 24/7 agents configured for different assets and market regimes on Solana spot markets. Put HODL to the test with Market Making (MM), Liquidity Providing (LP), or Osprey-based token trading. ## The HawkFi Thesis
Every retail investor is moving toward their own quant agent: AI-native, data-driven, always-on, and built for fully or semi-automated execution. HawkFi is building the terminal where those agents are created, tested, deployed, and improved. HawkFi started on Solana spot markets with agentic liquidity provision because crypto is the fastest form factor for tokenized markets. From there, the same agent stack expands into permissionless market making, systematic spot trading, perpetuals, and eventually the most traded assets globally: crypto, commodities, public equities, and private markets as they become tokenized. The goal is a factory of specialized agents that can run market-specific models at machine speed, around the clock, across asset classes and regimes. Each agent is a step toward generalized agent intelligence for trading any asset, in any regime, anywhere. {% hint style="info" %} HawkFi backtests, models, and agents help users compare strategies against HODL and passive benchmarks. They do not guarantee future returns or remove market risk. {% endhint %} ## What can you run? | Workflow | Use it when you want to | What HawkFi runs | | -------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------- | | [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | Run permissionless MM by placing and refreshing buy and sell quotes around price. | Dynamic Limit Order mechanics, execution models, inventory controls, and quote management. | | [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | Screen markets 24/7 and route qualified LP entries into a model. | Osprey screening, HawkFi Models, and LP position automations. | | [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) | Use eligible Osprey signals for direct token entries and full-position exits. | Osprey models, entry filters, capital limits, adaptive sizing, and token-trade exit controls. | | [Liquidity Providing with HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) | Run DLMM LP models that compete against passive LP and HODL. | Models and automations, with Laboratory backtests against passive LP and HODL benchmarks before live deployment. | ## How HawkFi grows HawkFi's first production edge is agentic liquidity on Solana: LP automation, market making, and benchmark-driven model selection on tokenized spot markets. The next layer is a broader agent platform for retail investors who want systematic execution without building quant infrastructure themselves. Users choose an asset, market regime, and strategy path. HawkFi supplies the models, simulation tools, agent workflows, and execution surfaces. | Layer | What it means | | ------------------------------ | --------------------------------------------------------------------------------------------- | | Agent Terminal | The user surface for testing, selecting, deploying, and monitoring agents. | | Specialized agents | Market Making, screening, LP, and token-trading agents tuned for specific assets and regimes. | | Models and simulations | Historical testing, benchmark comparison, and configuration research before live deployment. | | Generalized agent intelligence | The long-term direction: agents that can adapt across assets, venues, and market regimes. | ## Documentation Hierarchy HawkFi documentation is organized from terminal overview to execution: | Layer | Purpose | What lives there | | --------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | | [HawkFi overview](https://hawkfi.gitbook.io/whitepaper) | Explains HawkFi as an Agent Terminal for market making, LP, and token-trading workflows. | Core product identity, agent paths, and where to start. | | [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) | Explains 24/7 agents for market making, screened LP entries, and Osprey-based token trading. | Agent taxonomy, all three Agent types, setup flows, and advanced controls. | | [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) | Lets users test MM and LP configurations on historical pool conditions. | Market Making Mode, Liquidity Mode, metrics, backtests, and benchmark comparisons. | | [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) | Introduces LP models and helps users choose where to start. | Strategy picker, market scenarios, model overview, and LP model table of contents. | | [Build Your Own Strategy](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) | Explains the LP automation building blocks. | Auto-compound, Auto-accumulate, Auto-rebalance, Reshape Liquidity, Take Profit, and Stop Loss. | ## Start Here [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent)\ Choose among Market Making Agent, Screener Agent, and Osprey Trading Agent based on the job you want HawkFi to run. [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet)\ Fund the selected Agent workflow after choosing an Agent type and before activation. [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents)\ Start here if you want to deploy 24/7 agents for market making, screened LP entries, or Osprey-based token trades. [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory)\ Use Laboratory to backtest Market Making Agent configurations, LP models, and custom setups before deploying real capital. [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models)\ Use Models when you want a starting point for Liquidity Providing strategies across different market environments. [Build Your Own Strategy](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models)\ Use Build Your Own Strategy when you want to combine HawkFi automations manually instead of starting from a model. # Choose Your HawkFi Agent Choose among Market Making Agent, Screener Agent, and Osprey Trading Agent based on the job you want HawkFi to run. HawkFi Agents has three agent types: Market Making Agent, Screener Agent, and Osprey Trading Agent. Use this page to choose the live workflow before you fund or configure an agent. {% hint style="info" %} Before funding a Market Making Agent, check its [current access status](/whitepaper/market-making-agent/market-making-agents-mma). {% endhint %} ## What you will accomplish By the end of this guide, you should know which HawkFi Agent matches the job you want to automate and where to continue. | If you want HawkFi to | Choose | Why | | ------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | | Manage buy and sell quotes around price on a pool you already selected | [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | Uses Dynamic Limit Order mechanics to place and refresh maker quotes around price. | | Screen pools 24/7 and route qualified LP entries into a HawkFi execution model | [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | Uses Osprey for screening and entry discovery, then uses HawkFi Models and automations after entry. | | Use eligible Osprey signals for direct token entries and full-position exits | [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) | Uses Osprey models and user-configured filters, sizing, allocation, and exit controls to manage token trades. | | Test a setup before using live capital | [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) | Simulates Market Making Agent behavior or LP model behavior on historical pool conditions. | | Start from a model for a manually selected LP position | [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) | Provides execution models for different assets and market regimes. Models are not a separate Agent type. | ## Choose by task {% stepper %} {% step %} ### Decide whether you already know the pool Choose Market Making Agent when you already have a pool in mind and want live maker quotes around its price. Choose Screener Agent when you want Osprey to screen for qualified opportunities before HawkFi enters an LP position. Choose Osprey Trading Agent when you want eligible Osprey signals to become direct token trades within configured capital, filter, and exit limits. {% endstep %} {% step %} ### Match the workflow to the market Market Making Agent works best for sideways, range bound, consolidating, or neutral price action where live bid and ask quotes can operate around price. Screener Agent is for opportunity discovery. Osprey screens top pools continuously, then routes qualified entries into the selected HawkFi execution model. Osprey Trading Agent is for Osprey-based token trading. It uses the selected Osprey model and filters before entering a token trade from the agent's WSOL balance. {% endstep %} {% step %} ### Decide whether to test first Use HawkFi Laboratory before live deployment when you want to compare settings, study drawdown, inspect inventory behavior, or test whether a configuration fits a historical market window. Laboratory is a simulation product. It is separate from live HawkFi Agents. {% endstep %} {% step %} ### Continue to the matching setup * [Run a Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Find Opportunities with Osprey V2](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Run an Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) * [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) {% endstep %} {% endstepper %} ## How to know you chose the right path You should be able to answer three questions before continuing: 1. Do you want HawkFi to manage quotes, open screened LP positions, or manage direct token trades? 2. Which market behavior makes that workflow appropriate? 3. Will you test the setup in Laboratory before using live capital? ## Go deeper * [Meet HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) * [Test Before You Deploy](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) * [Explore HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) # Fund Your Agent Wallet Fund the selected HawkFi Agent workflow before activation. Funding depends on the Agent type. Market Making Agent and Screener Agent use the shared Agent funding flow. Osprey Trading Agent receives its configured trading allocation in an isolated WSOL account when the agent is created. Choose the Agent type before funding so the capital follows the correct workflow. {% hint style="info" %} Connecting your wallet lets you sign transactions and control your Agents. HawkFi cannot control your wallet because HawkFi Agents are designed to be self-custodial. {% endhint %} ## Before you begin | Check | Why it matters | | -------------------------- | ---------------------------------------------------------------------------------------------------- | | Choose an Agent type | Market Making Agent, Screener Agent, and Osprey Trading Agent use funds differently. | | Decide your working amount | The amount should match the position size, open-position limits, or inventory you plan to configure. | | Keep a SOL reserve | The Agent wallet needs SOL for the Agent workflow and network activity. | | Review fees and risk | Funding an Agent does not guarantee fills, entries, or returns. | {% hint style="info" %} Check the [Market Making Agent reference](/whitepaper/market-making-agent/market-making-agents-mma) for its current access and funding requirements. Screener Agent funding should cover the fixed position size and the number of positions you allow it to open. Osprey Trading Agent uses `Create Agent and Deposit` to fund its configured `Maximum agent allocation` from the connected wallet. The app's shared `Agents Fund` supplies and receives temporary-account rent; it does not hold Osprey Trading Agent principal. {% endhint %} ## Fund the Agent wallet {% stepper %} {% step %} ### Open HawkFi Agents and connect your wallet [Open HawkFi Agents](https://www.hawkfi.ag/agents), then connect the wallet that will authorize your Agent actions. {% endstep %} {% step %} ### Open the funding flow for your Agent type For Market Making Agent or Screener Agent, find `Agents Fund` in the HawkFi Agents interface. For Osprey Trading Agent, open `New Agent`, select `Osprey Trading Agent`, and configure the agent before funding it with `Create Agent and Deposit`. {% endstep %} {% step %} ### Add the amount you plan to allocate For Market Making Agent, fund enough inventory for the quote setup you plan to run and keep the required SOL reserve. For Screener Agent, align funding with the fixed position size, maximum open positions, and maximum pools in your Entry Settings. For Osprey Trading Agent, confirm that `Maximum agent allocation` covers `SOL per entry` across `Maximum open trades`. The creation flow deposits that allocation into the agent before activation. {% endstep %} {% step %} ### Confirm the funded balance Wait for the transaction to confirm. For Market Making Agent or Screener Agent, check the updated `Agents Fund` balance before activation. For Osprey Trading Agent, confirm that its portfolio balance appears in the Agents table after creation and activation. {% endstep %} {% step %} ### Continue to Agent setup * [Run a Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Find Opportunities with Osprey V2](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Run an Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) {% endstep %} {% endstepper %} ## How to know it worked The relevant balance should show the funded amount: `Agents Fund` for Market Making Agent or Screener Agent, or the Osprey Trading Agent portfolio balance after creation. Confirm that the amount matches the Agent settings you plan to use. ## Go deeper * [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) * [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) # Tutorial Library Watch HawkFi tutorial videos and open the related product documentation when you need more detail. Watch all HawkFi tutorial videos on this page. Each video includes a link to the relevant product documentation when you want to read more. ## HawkFi Laboratory ### Optimize Market Making Agents in Laboratory {% embed url="" %} Learn how to test and optimize Market Making Agent configurations in HawkFi Laboratory before using the setup in live execution. Read more: [Market Making Laboratory](/whitepaper/hawkfi-laboratory/market-making) ## HawkFi Market Making Agent ### Create a Market Making Agent {% embed url="" %} Learn how to create a Market Making Agent, choose the setup inputs, and prepare the agent before launch. Read more: [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) ### Understand Market Making Agent profit drivers {% embed url="" %} Learn how quote behavior, market conditions, and configuration choices affect Market Making Agent results. Read more: [Execution models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) ## HawkFi Screener Agent (Osprey V2) ### Create a Screener Agent with Osprey {% embed url="" %} Learn how to start from the New Agent page, choose the current `Osprey LP Screener Agent` app option, and prepare the Screener Agent setup flow. Read more: [Screener Agent (Osprey V2)](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) ## Liquidity providing tutorials ### Auto-rebalance up-only for LP positions [Watch on X](https://x.com/bradydonut/status/1838819174417863109) Read more: [Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar) ### Use LP analytics to measure automation profitability [Watch on X](https://x.com/bradydonut/status/1839311022529851700) Read more: [Liquidity Providing Laboratory](/whitepaper/hawkfi-laboratory/liquidity-providing) ### DCA into tokens while earning fees [Watch on X](https://x.com/bradydonut/status/1839634764170703328) ### Automate Take Profit and Stop Loss [Watch on X](https://x.com/bradydonut/status/1843917642081677801) Read more: [Take Profit](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/take-profit-tp) and [Stop Loss](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/stop-loss-sl) {% hint style="info" %} The product documentation contains the full mechanics, settings, and references. Use the links below each video when you want to read more. {% endhint %} # HawkFi Agents Deploy 24/7 quant agents for market making, screened liquidity providing, and Osprey-based token trading. ## What are HawkFi Agents? HawkFi Agents are 24/7 quant agents built to run market making, screened liquidity providing, Osprey-based token trading, execution models, and liquidity automations. They are the deployable layer of the HawkFi Agent Terminal. Use Agents when you want a machine-speed system that can keep operating around a configured market view instead of managing every quote, screen, entry, and automation manually. ## Why HawkFi Agents The next wave of retail investors will be AI-native, data-driven, and always-on. HawkFi Agents are built for that user: someone who wants specialized agents for specific assets, venues, and market regimes. Market Making Agent focuses on MM through Dynamic Limit Order quoting. Screener Agent uses Osprey to screen opportunities and route qualified entries into HawkFi Models. Osprey Trading Agent uses eligible Osprey signals to enter and manage direct token trades. Each specialized Agent expands the factory toward broader agent intelligence across spot, perps, and tokenized markets. ## How it fits with HawkFi Agents Each HawkFi Agent handles a different part of the trading workflow: | Agent type | What it does | | ------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- | | [Screener Agent](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | Uses Osprey to find qualified opportunities, then opens and manages LP positions with HawkFi Models. | | Osprey Trading Agent | Uses eligible Osprey signals to enter and exit direct token trades. | | [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | Manages live bid and ask quotes around the market price. | ## Agent Types HawkFi Agents currently has three agent types: | Agent type | Current app label | Purpose | What it does | | ------------------------------------------------------------------------------------- | -------------------------- | ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------- | | [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | `Market Making Agent` | Permissionless Market Making | Uses Dynamic LO mechanics to manage buy and sell quotes around price on a pool. | | [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | `Osprey LP Screener Agent` | Quant-optimized Dynamic Liquidity Market Making | Uses Osprey V2 and HawkFi Models to screen for runner opportunities and route qualified LP entry. | | [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) | `Osprey Trading Agent` | Osprey-based token trading | Uses eligible Osprey signals, user-configured filters, capital limits, and full-position exits to manage token trades. | ## Documentation Hierarchy HawkFi Agents documentation is organized from product overview to agent type: | Layer | Purpose | What lives there | | ------------------------------------------------------- | ----------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | | HawkFi Agents | Introduces the three agent types and helps users choose where to start. | Product overview, agent philosophy, and where Agents fit in the HawkFi Agent Terminal. | | Agent type page | Explains one agent type in more detail. | What it is for, how it works, core building blocks, setup flow, and related HawkFi surfaces. | | Agent type's advanced settings or Agent specific models | Explains a deeper setup concept inside one agent type. | Examples: Market Making Agent Execution Models and Advanced Settings. | ## Start Here [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent)\ Choose among Market Making Agent, Screener Agent, and Osprey Trading Agent based on the job you want HawkFi to run. [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet)\ Fund the selected Agent workflow before creating or activating a live Agent. [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma)\ Market Making Agent is the next page after this overview. It explains HawkFi's agent for managing buy and sell quotes around price. [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1)\ Screener Agent uses Osprey V2 for the 24/7 screening flow that can be selected from the New Agent page. [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent)\ Osprey Trading Agent uses eligible Osprey signals for direct token trades with configured entry, allocation, filter, and exit controls. [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory)\ HawkFi Laboratory is the experimenting and benchmarking tool for strategies, HawkFi models, and HawkFi agent configurations. [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent)\ Check Agent balances, live behavior, open positions, and the settings that may need attention after launch. ## Related Pages * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) # Monitor and Manage Your Agent Check Agent balances, live behavior, open positions, and the settings that may need attention after launch. Use the HawkFi Agents page to check how much capital is deployed, what the Agent is doing, and whether its current behavior still fits the setup you intended. ## What to monitor | Agent type | Start with | What to check | | -------------------- | -------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | | Market Making Agent | `Agent Portfolio`, the Agents table, and the Dynamic Limit Order dashboard | Vault value, idle inventory, open-order value, bid and ask placement, fills, markout, and inventory drift. | | Screener Agent | The Agents table and shared Open Positions table | Whether Osprey has opened a position, position value, unclaimed fees, unrealized PnL, and the position management or exit rules attached to the setup. | | Osprey Trading Agent | The Agents table and shared Open Positions and Closed Positions tables | Agent portfolio balance, open and closed trades, entry and exit transactions, unrealized or realized PnL, and manual exit controls. | ## Share your results Open a PNL Card from a supported Agent row by clicking `PROFIT`, or select `PNL Card` in Market Making Agent Analytics. Switch between USD and SOL, hide or show stats, then download or copy the image. ## Monitor a Market Making Agent `Agent Portfolio` includes Market Making Agent vault funds in `Deployed`. This includes idle inventory and value currently locked in open orders. Market Making Agent rows in the Agents table show total vault value and a per-token breakdown in the `BALANCE` column. For a newly funded Market Making Agent, `PROFIT` and `HODL` show `-` until the first scored fill. This avoids treating funded but not-yet-quoted capital as a loss. ### Read the Agent Health indicator Funded Market Making Agent rows show a performance status under the agent name. The status follows the selected USD or SOL display and compares the agent with HODL in that currency. | Status | What it means | | ------------- | --------------------------------------------------------------------------------------------------------------------- | | `New` | The agent started less than one hour ago and is still establishing a track record. | | `Healthy` | The agent has positive PnL, is ahead of HODL, or does not yet meet a `Needs watch` condition. | | `Needs watch` | The agent has negative PnL and either trails HODL by more than 25%, or HODL has remained ahead for at least 48 hours. | | `Stopped` | The agent is paused or archived. | Screener Agents do not show this indicator. A Market Making Agent also shows no indicator when comparison data is not available yet. Agent Health summarizes relative performance; it does not guarantee future results or report infrastructure health. On the Dynamic Limit Order dashboard, bid and ask visuals use the same colors across the chart and bin display: | Visual | Meaning | | ------ | ---------- | | Blue | Bid quotes | | Orange | Ask quotes | Use Market Making Agent Analytics and HawkFi Laboratory to decide whether the execution model still fits the pool. | What you see | What it can mean | | --------------------------------- | ------------------------------------------------------------------------------------------------ | | Too few fills | Orders may be too wide, the pool may be inactive, or the selected model may be too defensive. | | Too many bad fills | Orders may be too tight, momentum may be one-sided, or the pool may need a more defensive model. | | Inventory drifts too far | Inventory skew, split, utilization, or model defensiveness may need adjustment. | | High activity without better edge | Quote cadence, requote threshold, or spread factor may be too aggressive. | {% hint style="info" %} Test material changes in HawkFi Laboratory before making a live Market Making Agent configuration more aggressive. {% endhint %} ## Monitor a Screener Agent Screener Agent rows leave the Agents table `BALANCE` cell blank. Positions opened by Screener Agents appear in the shared Open Positions table. `UNCLAIMED FEES` applies to Screener Agent LP positions. It does not apply to Osprey Trading Agent token trades or Market Making Agent open orders. `UNREALIZED PNL` can appear for Screener Agent LP positions and Osprey Trading Agent open trades. In each case, it describes that LP position or token trade. It does not describe Market Making Agent open orders. If `Osprey V2 High Volume 5M (Selective)` has not opened a position, that does not automatically mean the Agent is broken. The model is selective by design and waits for higher confidence entries instead of forcing constant positions. ## Monitor an Osprey Trading Agent Osprey Trading Agent rows show a portfolio balance based on the agent's WSOL and current token accounts. Use the positions shortcut on the Agent row to scope the shared position tables to that agent. Open trades show the token, age and Agent name, current token balance, original entry price, `UNREALIZED PNL`, and an entry transaction link. Select `EXIT` to review a full-position swap back to the agent's WSOL account. Closed trades show the trade age, Agent name, `REALIZED PNL`, closure time, and `ENTRY` and `EXIT` transaction links. {% hint style="info" %} Osprey Trading Agent trades are token swaps. They do not use the Screener Agent LP columns for `UNCLAIMED FEES` or LP position management. {% endhint %} ## Manage the next change {% stepper %} {% step %} ### Identify the behavior you want to change Separate a funding issue, a market-fit issue, and a configuration issue before changing settings. {% endstep %} {% step %} ### Open the canonical setting reference For Market Making Agent, review [Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) and [Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings). For Screener Agent, review the [Entry Settings, position management, and exit flow](/whitepaper/lp-screener-agent/screener-agents-osprey-v1#quick-start-tutorial). For Osprey Trading Agent, review its [entry, allocation, filter, and full-position exit controls](/whitepaper/trading-agent/osprey-trading-agent#current-settings-reference). {% endstep %} {% step %} ### Test the change when possible Use [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) to compare a Market Making Agent configuration or LP model against the same historical pool conditions before live deployment. {% endstep %} {% step %} ### Change one decision at a time Keep the reason for the change clear so you can tell whether the new behavior came from the execution model, advanced settings, position management, or exit rules. {% endstep %} {% endstepper %} ## Go deeper * [Choose an Execution Model](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) * [Tune Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) * [Find Opportunities with Osprey V2](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Run an Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) * [Move from Backtest to Live](/whitepaper/hawkfi-laboratory/move-from-backtest-to-live) * [Solve Common Problems](/whitepaper/guides-and-support/faqs) # Market Making Agent Run permissionless Market Making with agentic "grid trading" across Solana spot assets and market regimes Market making on Solana used to be reserved for prop AMMs, trading firms, and teams with custom infrastructure.\ \ HawkFi Market Making Agent brings that workflow into HawkFi Agents, with optimized models, Dynamic LO execution, and 0% execution cost for Agents funded with more than $500.
## What is the HawkFi Market Making Agent? The Market Making Agent is a HawkFi Agent type designed to bring institutional-style market making to HawkFi users. Users with access can deploy and customize HawkFi Market Making Agents that continuously place buy orders just below the current price and sell orders just above the current price on a pool, such as SOL-USDC, cbBTC, whETH, ZEC, JUP, JLP, MET, JTO, or HYPE. {% hint style="info" %} Market Making Agent is in live private beta and currently uses a DM-led selective rollout. If you have access, [open the New Agent page](https://www.hawkfi.ag/agents/new) and choose Market Making Agent. {% endhint %} ### How is it possible? Under the hood, Market Making Agents use a live ladder of resting **Dynamic Limit Orders (DLO)** on Meteora DLMM. These are not static rule-based bots. The execution models are tuned for different market regimes and asset classes, so spread, refresh tempo, and inventory skew can adapt to what each asset is actually doing. {% hint style="info" %} For simplicity, users can deploy optimized models for their agents. Advanced users can also customize Market Making Agent with [Advanced Settings.](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) {% endhint %} ### How do you earn? {% hint style="success" %} from 100% of the PnL spread (Markouts), at 0% execution cost for Agents funded with more than $500. {% endhint %} When the agent places quotes, it tries to buy slightly below the current price and sell slightly above the current price. If fills are clean and market conditions cooperate, the difference between those fills can become spread PnL, also called markout. {% hint style="info" %} Market Making Agents can be a useful alternative to LPing when a token pool has low fees, low volume, or too much competition from prop AMMs. In those markets, earning from spread PnL may be more attractive than competing for low LP fee capture. {% endhint %} ## Market Making Agent Overview | Agent | Details | | ------------ | ------------------------------------------------------------------------------------------------------------------- | | Best for | Sideways, range bound, consolidating, or delta neutral markets where the user wants live maker quotes around price. | | How it works | Places and refreshes buy and sell orders around the current pool price through Dynamic Limit Orders mechanics. | ### General Guidelines | Category | Remarks | | ----------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best market shape | Sideways, range bound, consolidating, or neutral price action. | | Ideal assets: |

Crypto: SOL-USDC, cbBTC, whETH, ZEC, JUP, JLP, MET, JTO, and HYPE.

Experimental or thinner examples to test carefully first: CARDS, PUMP, and PUMPCADE.

| ## Market Making Agent Building Blocks | Building block | What it controls | | ----------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Agent Settings | Choosing the pool, deposit size, execution model, inventory split, order count, spread factor, and **optional Advanced Settings.** | | Inventory Funding | Adds the funds the agent will use for market making, plus the SOL reserve needed to run. | | Quote Management | Reviews how many buy and sell orders the agent can place, how much inventory it can use, and when orders should be replaced. | | Lifecycle | Reviews the final setup, confirm funding, and create the agent. | {% hint style="success" icon="circle-info" %} **Execution Models** are responsible to how wide or tight the Market Making Agent will be.\ \ Learn more about [Execution models here](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) {% endhint %} {% hint style="info" %} **Advanced Settings** are available for users who want more control over quote placement, signal behavior, sizing, and requote rules.\ \ Learn more about [Advanced Settings here](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) {% endhint %} ## Monitoring balances after launch The Agents page shows Market Making Agent capital in two places: | Surface | What it shows | | ----------------------------- | ------------------------------------------------------------------------------------------------------------------------- | | `Agent Portfolio` | `Deployed` includes Market Making Agent vault funds, including idle inventory and value currently locked in open orders. | | Agents table `BALANCE` column | Market Making Agent rows show the total vault value and a per-token breakdown. Screener Agent rows leave this cell blank. | Use these values to check how much capital is committed to Market Making Agents after funding or order activity. The shared Open Positions table also includes columns used by Screener Agent LP positions. `UNCLAIMED FEES` and `UNREALIZED PNL` describe positions opened by Screener Agents, not Market Making Agent open orders. On the Dynamic Limit Order dashboard, bid and ask visuals follow the same color convention across the chart and bin display: | Visual | Meaning | | ------ | ---------- | | Blue | Bid quotes | | Orange | Ask quotes | ## How to deploy HawkFi Market Making Agents Use this simplified walkthrough to create a Market Making Agent {% stepper %} {% step %} #### Visit HawkFi Agents and connect your wallet.
Connecting your wallet lets you sign transactions and control your agents. Your connected wallet authorizes actions for your agents and agent wallet.\ \ HawkFi cannot control your Wallet since they are designed to be self-custodial. {% endstep %} {% step %} #### Fund your Agent wallet
Agent wallets are designed so you can allocate SOL based on the amount you want the agent to use.\ \ The current minimum to use HawkFi Market Making Agent efficiently is 1 SOL. See [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) for the shared funding checklist. {% endstep %} {% step %} #### Click on the New Agents button
{% endstep %} {% step %} #### Select Market Making Agent
Market Making Agent works best for pools with consolidated, range bound, sideways, or neutral price action. {% endstep %} {% step %} #### Select the Pool
Search the pair or paste the pool address you want to market make. Example pools and assets include SOL-USDC, cbBTC, whETH, ZEC, JUP, JLP, MET, JTO, and HYPE. For thinner or more speculative pools such as CARDS, PUMP, or PUMPCADE, test in HawkFi Laboratory first and start with a more defensive Execution Model. {% endstep %} {% step %} #### Configure your Market Making Agent
Select your `Execution Model`\ \ Use `SOL Wide` or `SOL Tight` for SOL-USDC. For other assets, start with `Blue Chip General`, `Mid-Cap`, `Small-Cap`, or `Micro-Cap` based on the token's market-cap category.\ \ The selected model applies its starting quote-placement and inventory-hedging defaults. You can adjust the settings before creating the agent.\ \ You can hover on each Market Making Agent configuration tooltip to learn what each setting controls. {% endstep %} {% step %} #### Create Agent and Deposit
Review the settings, confirm the funding step, then create and deposit into the agent. {% endstep %} {% endstepper %} {% hint style="info" %} HawkFi Laboratory is the best place to test Market Making Agent behavior before making a live configuration more aggressive. {% endhint %} ## FAQs for HawkFi's Market Making Agents
What's the minimum deposit to start? 1 SOL
## Fees HawkFi keeps Market Making Agent fees simple: {% hint style="success" %} 0% fees for Market Making Agents funded with more than $500. {% endhint %}
Detailed fee table | Funded amount | Automation cadence | Fee per fill | | -------------- | ------------------- | -------------- | | Less than $50 | No automation tier | Not applicable | | $50 to $500 | 5-minute automation | 5 bps | | More than $500 | 5-minute automation | 0 bps |
## Related Pages * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) * [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) * [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) * [Market Making Agent Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) * [Market Making Agent Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) * [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) ## More Questions? * Join our Discord for questions and discussions on HawkFi: # Execution models Choose the starting quote behavior for a HawkFi Market Making Agent. Execution Models set how a Market Making Agent starts placing quotes. Choose a model based on the pool and asset category, then adjust settings if you want a different balance between fill opportunity and protection. Selecting a model applies its default quote-placement and inventory-hedging settings. It is a starting configuration, not a locked strategy. ## Current Execution Models | Execution Model | Use it for | Starting behavior | | ------------------- | -------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | | `SOL Wide` | SOL-USDC when you prefer more distance from the current price. | Starts with wider quote placement and a more defensive fill posture. | | `SOL Tight` | SOL-USDC when you want quotes closer to price. | Starts with tighter quote placement for more fill opportunity, with greater adverse-selection risk. | | `Blue Chip General` | Non-SOL assets with a market cap of $1B or more. | Uses quote distances that adjust to the selected pool’s DLMM bin step, so the model keeps a similar quote posture across blue-chip pools. | | `Mid-Cap` | Assets with a market cap from $100M to $1B. | Starts with a balanced posture for active pools with less depth than blue chips. | | `Small-Cap` | Assets with a market cap from $10M to $100M. | Starts more defensively to account for thinner liquidity and faster inventory movement. | | `Micro-Cap` | Assets with a market cap below $10M. | Starts with the most defensive defaults for sparse and more volatile liquidity. | ## Choosing an Execution Model Market cap is a starting guide for the non-SOL models: | Category | Market-cap range | | ----------- | ---------------- | | `Micro-Cap` | Under $10M | | `Small-Cap` | $10M to $100M | | `Mid-Cap` | $100M to $1B | | Blue Chip | $1B and above | Pool liquidity, volume, fee tier, and current price behavior still matter. Test a configuration in HawkFi Laboratory before making a live agent more aggressive. ## Active inventory hedging After a one-sided fill, active inventory hedging can pause quotes and use spot liquidity to rebalance inventory when the selected model’s profit conditions are met. | Execution Model | Rebalance time check | Minimum markout | Early markout | | ------------------- | -------------------- | --------------- | ------------- | | `SOL Wide` | 45 minutes | 5 bps | 40 bps | | `SOL Tight` | 30 minutes | 5 bps | 50 bps | | `Blue Chip General` | 30 minutes | 10 bps | 100 bps | | `Mid-Cap` | 20 minutes | 15 bps | 250 bps | | `Small-Cap` | 15 minutes | 20 bps | 400 bps | | `Micro-Cap` | 10 minutes | 25 bps | 600 bps | Users can adjust these controls or turn active inventory hedging off in [Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings). ## Current model defaults Quote distances scale with the selected pool’s DLMM bin step, so each current Execution Model keeps its intended quote posture across pools. Existing agents retain their saved configuration and are not automatically migrated when model defaults change. ## Related Pages * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Market Making Agent Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) * [HawkFi Laboratory: Market Making](/whitepaper/hawkfi-laboratory/market-making) * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) # Advanced Settings Tune how cautious, aggressive, or selective the agent should be when placing orders Advanced Settings are for HawkFi Market Making Agents users who want to tune how cautious, aggressive, or selective the agent should be when placing orders. Most users can start with an Execution Model default, then adjust advanced parameters only when they understand the tradeoffs. ## Where Advanced Settings fit Advanced Settings belong conceptually under Agent Settings. They change how the agent places, sizes, refreshes, filters, and protects quotes before the agent is funded and launched. They do not replace Execution Models. Execution Models choose the baseline behavior. Advanced Settings let experienced users tune that behavior. {% hint style="info" %} If you are not sure what a parameter does, start with the Execution Model default and test changes in HawkFi Laboratory before using a more aggressive live configuration. {% endhint %} ## Setting Groups | Setting group | What it controls | | ----------------- | ------------------------------------------------------------------------------------------------------------------ | | Placement toggles | Adaptive placement and requote-on-fill behavior. | | Placement | Base spread, level spacing, volatility spread, and max spread. | | Signals | Fair value lookback, mean reversion, directional lookback, directional bias, and directional offset. | | Momentum | Momentum lookback, momentum threshold, momentum spread, and toxic-side size. | | EV Gate | Minimum edge, fair value weight, and penalties for risky conditions. | | Sizing | Minimum size, inventory skew, Stoikov gamma, max side size, minimum order value, fee share, and quote update cost. | | Inventory hedge | Whether filled inventory can be rebalanced and the timing and profit thresholds used. | | Requote | Requote threshold and maximum order age. | ## Placement Placement settings control where quotes sit around the current price and how the agent responds when market conditions change. | Setting | Plain meaning | | ------------------- | ----------------------------------------------------------------------------------------------------------------------- | | Adaptive placement | Allows the agent to adjust placement as market conditions change. | | Requote on fill | Refreshes quote placement after a fill. | | EV gate | Turns expected-value gating on or off. When enabled, the agent can require a minimum expected edge before placing size. | | Markout horizons | Sets the time windows the model uses to evaluate post-fill quality. | | Base spread | Sets the starting quote distance from the current price. | | Level spacing | Controls spacing between quote levels when using multiple bids and asks. | | Volatility lookback | Looks back across recent steps to estimate how noisy the market is. | | Volatility spread | Widens quotes when volatility is higher. | | Max spread | Caps how far the agent can widen quotes. | ## Signals Signal settings help the agent decide whether the current price action is clean enough to quote or whether it should become more selective. | Setting | Plain meaning | | --------------------- | ----------------------------------------------------------------------- | | Fair value lookback | Looks back to estimate where fair value may be. | | Mean reversion | Adjusts behavior when price may be reverting toward fair value. | | Mean reversion offset | Controls how much the agent offsets quotes for mean reversion behavior. | | Directional lookback | Looks back for directional movement. | | Directional bias | Controls how strongly directional movement affects quote placement. | | Directional offset | Caps how much directional bias can move quotes. | ## Momentum Momentum settings help protect the agent from one-sided or fast-moving price action. | Setting | Plain meaning | | ------------------ | --------------------------------------------------------------- | | Momentum lookback | Checks recent price movement for momentum. | | Momentum threshold | Sets how much movement is needed before momentum logic matters. | | Momentum spread | Widens quotes when momentum risk increases. | | Toxic-side size | Reduces quote size on the side most exposed to toxic fills. | ## EV Gate EV Gate settings help the agent require more expected edge before taking risk. | Setting | Plain meaning | | ------------------ | ------------------------------------------------------ | | Min edge | Sets the minimum expected edge before quoting. | | Fair value weight | Controls how much fair value influences expected edge. | | Momentum penalty | Penalizes quoting into risky momentum. | | Volatility penalty | Penalizes quoting when volatility is too noisy. | | Inventory penalty | Penalizes quotes that worsen inventory imbalance. | | Full-size edge | Sets the edge needed before using larger quote size. | ## Sizing Sizing settings control how much the agent places on each side. | Setting | Plain meaning | | ---------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- | | Min size | Sets the minimum quote size behavior. | | Inventory skew | Adjusts quote behavior when the agent holds too much of one side. | | Stoikov gamma (experimental) | Shifts the center of the bid and ask ladder away from excess inventory. `Off` preserves the existing quote center; higher values create a stronger shift. | | Max side size | Caps how large one side of the quote ladder can get. | | Min order value | Sets the minimum order value the agent should place. | | Fee share | Controls the fee share assumption used by the agent. | | Quote update cost | Estimates the cost of updating quotes. | `Stoikov gamma (experimental)` ranges from `Off` to `1.0` and is off by default. It changes quote prices, while `Inventory skew` changes the relative size placed on each side. Test positive gamma values in HawkFi Laboratory before using them in a live configuration. ## Inventory hedge Active inventory hedging is enabled by default for the six selectable Execution Models. It can pause quotes and use spot liquidity to rebalance filled inventory when the configured profit conditions are met. | Setting | Plain meaning | | ---------------------------- | --------------------------------------------------------------------------------------- | | Use active inventory hedging | Turns automatic inventory recovery on or off. Turning it off is saved for that agent. | | Rebalance time check | Sets how long an unmatched fill must remain before the agent can use `Minimum markout`. | | Minimum markout | Sets the protected profit required to rebalance after the time check. | | Early markout | Sets the higher protected-profit requirement used before the time check. | The default timing and markout values depend on the selected Execution Model. See [Market Making Agent Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) for the current model table. ## Requote Requote settings control when old quotes should be replaced. | Setting | Plain meaning | | ----------------- | ---------------------------------------------- | | Requote threshold | Replaces quotes when price moves too far away. | | Max order age | Replaces quotes after they stay live too long. | ## Related Pages * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Market Making Agent Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) # Screener Agent (Osprey V2) 24/7 Screener Agent that catches \~70% of daily runners and deploys LP automatically Most token opportunities are easy to miss manually. Tokens move fast, rotate fast, and often become obvious only after the best entry window is gone. HawkFi Screener Agent brings 24/7 screening into HawkFi Agents, using Osprey to catch runners early and execute battle-tested models. ## What is the HawkFi Screener Agent? The Screener Agent is a HawkFi Agent type that brings 24/7 screening using Osprey to catch runners early and execute battle-tested quant models. {% hint style="success" %} The HawkFi Screener Agent's core is **Osprey** {% endhint %} ## Quick Start Tutorial {% hint style="info" %} As of June 29, 2026, `Osprey V2 High Volume 5M (Selective)` catches \~**70% of daily runners** in the current beta benchmark.\ \ Agent improvements are expected over time. {% endhint %} {% embed url="" %} Use this simplified walkthrough to create a Screener Agent with Osprey selected in the Entry Model field. {% stepper %} {% step %} #### Fund the Agent wallet. Add SOL to your `Agents Fund` before turning the agent live. {% endstep %} {% step %} #### Configure Entry Settings. Set the agent name, fixed position size, maximum open positions and pools, re-entry cooldown, pool selection criteria, and optional extra filters. {% endstep %} {% step %} #### Pick the Screening agent (Osprey V2) Choose an Osprey model as the Screening Agent. `Osprey V2 High Volume 5M (Selective)` remains the default. Osprey V2 is designed to catch runners early by screening top pools 24/7 for opportunities most humans would miss. {% endstep %} {% step %} #### Pick your Execution Model. Choose how HawkFi should execute once Osprey finds an opportunity.\ \ HawkFi screening agents use HawkFi's models as Execution Models Want to dive deeper on Screener Agent Execution Models? See [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endstep %} {% step %} #### Choose Position Management settings. Add optional HawkFi automations such as Auto-Compound, Auto-Accumulate, Auto-Rebalance, or Reshape Liquidity if the position should keep managing itself after entry.\ \ Position Managements uses HawkFi's Automations.\ \ Wanna learn more about HawkFi automations? See [Automations here.](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) {% endstep %} {% step %} #### Set your Exit Settings (TP and SL) Decide whether you want to exit positions manually, use basic take profit and stop loss targets, or create custom advanced exit logic.\ \ Exit Settings use HawkFi's automations.\ \ Wanna learn more about HawkFi automations? See [Automations here.](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) {% endstep %} {% step %} #### Review and launch. Confirm the agent wallet funding, Entry Settings, Entry Model, Execution Model, position management, and exit rules before activating the agent. {% endstep %} {% endstepper %} ## What is Osprey? Osprey is the screening agent inside HawkFi Screener Agent, designed to catch runners early by screening top pools 24/7 for opportunities most humans would miss. It stays awake around the clock, watches token activity, catches daily runners, and routes winning opportunities into HawkFi agents. {% hint style="info" %} This page covers the Screener Agent LP workflow. [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) is a separate HawkFi Agent type that uses eligible Osprey signals for direct token trades. {% endhint %} ### The Osprey V2 Agents #### Choose an Osprey model Screener Agent offers three Osprey models. Selective remains the default. | Model | Entry approach | | -------------------------------------- | ----------------------------------------------------------------------------------------------------- | | `Osprey V2 High Volume 5M (Selective)` | Fewer, highest-confidence entries. | | `Osprey V2 High Volume 5M (Degen)` | Broader coverage, more entries, and higher risk. | | `Osprey Edge` | Balanced opportunity and risk. It uses ML-powered signal ranking to guide entry selection and sizing. | #### Published Osprey benchmark studies
AgentBenchmarkAvg Entries / DayAvg. Losing StreakOptimized ForBehaviorStatus
Osprey High Volume 5M V17d: Catches ~67% of daily runners

14d: Catches 52% based on latest 14 days study		~10/day2Runner detectionScreens high activity pools and only enters when agent sees a qualified runner setupDeprecated
Osprey V2 High Volume 5M (Selective)14d: Catches ~70% of daily runners~3/day1.20High confidence opportunitiesPrioritizes stronger setups with fewer, more focused entries.Live beta
Osprey V2 High Volume 5M (Degen)14d: Catches ~62% of daily runners~6/day1.67Broader market opportunity coveragePrioritizes maximum opportunity coverage with faster, less selective entries.Live beta
{% hint style="info" %} **Benchmark Methodology**\ \ Benchmark results, as of June 29, 2026, are evaluated using a comprehensive 14-day historical study incorporating the latest agent improvements. Previous Osprey High Volume 5M V1 results (67% Runner Capture) were evaluated using an earlier 7-day benchmark. {% endhint %} #### What counts as a runner A runner is a top opportunity that Osprey was expected to catch. In this context, a top opportunity means a token represented by one of the highest-ranking HawkFi pools in the evaluation snapshot. These pools are usually ranked by recent pool fees, such as the latest 24-hour fees. The benchmark maps each pool to its subject token, excludes denominator assets where appropriate, and checks whether the filtered high-volume agent alerted that token inside the report window. In simple terms: ``` A runner is a top-pool token Osprey should have caught. ``` #### Current HawkFi Benchmarking Study Osprey currently catches 70% of daily runners in the beta benchmark. Osprey is not being framed around how many alerts it sends. It is being framed around how many runners it catches before they become obvious. ``` Runners caught = daily runners caught by Osprey / all eligible daily runners ``` The simple read: Osprey finds the market while humans are still watching scattered token feeds, pool pages, and noise. {% hint style="info" %} The 70% figure is the current beta benchmark for runners caught with `Osprey V2 High Volume 5M (Selective)`\ \ Agent improvements are expected over time. {% endhint %} ## Why use Osprey Most token opportunities are easy to miss manually. Tokens move fast, rotate fast, and often become obvious only after the best window is gone. HawkFi made the Osprey agent to built that gap. It monitors the market continuously 24/7, applies a repeatable screening, and catches a meaningful share of the daily runner universe before manual monitoring would usually react. {% stepper %} {% step %} ### Easy & Instant No manual setup, coding, or stitching tools together. Osprey is live inside HawkFi agents and can be configured in clicks. {% endstep %} {% step %} ### Quant Optimized No guesswork. Osprey is benchmarked against runners caught, win rate, and PnL outperformance studies, with an agent that can keep learning and improving over time. {% endstep %} {% step %} ### Battle Tested Execution Osprey routes opportunities into HawkFi's high frequency LP execution stack, built on one of the most proven LP automation engines on Solana.. {% endstep %} {% endstepper %} ## Screener Agent Building Blocks | Setup step | What it controls | | ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Entry Settings | Choose the agent name, fixed position size, maximum open positions, [**screening agent (Osprey V2)**](#what-is-osprey), re-entry cooldown, pool selection criteria, optional extra filters, and [execution models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) | | Initial Deposit | Choose the starting liquidity shape HawkFi should use after Osprey finds a matching opportunity. A position can use up to 250 total bins, including the active bin, with up to 249 bins on one side when the other side is empty. | | Position Management | Add optional [automations](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) such as Auto-Compound, Auto-Accumulate, Auto-Rebalance, or Reshape Liquidity. | | Exit Settings | Choose exit [automations,](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) basic TP/SL, or custom advanced exit logic. | ### Optional extra filters for Entry Settings | Filter | What it controls | | --------------------- | ------------------------------------------------ | | Market cap | Filters opportunities by token market cap. | | Token liquidity | Filters opportunities by token-level liquidity. | | Age | Filters opportunities by token age. | | Jupiter Organic Score | Filters opportunities by Jupiter Organic Score. | | 5m volume | Filters opportunities by recent 5-minute volume. | | Fees | Filters opportunities by fee activity. | | Pool TVL | Filters opportunities by pool-level TVL. | | Base fee | Filters opportunities by pool base fee. | | Bin step | Filters opportunities by pool bin step. | {% hint style="success" icon="circle-info" %} Screener Agent uses HawkFi models as its Execution Models\ \ Learn more about [Execution models for Screener Agent here](/whitepaper/models-and-automations-library/hawkfi-models) {% endhint %} {% hint style="warning" icon="circle-info" %} Position Management and Exit Settings use HawkFi Automations\ \ Learn more about [HawkFi automations here](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) {% endhint %} ## FAQs for Screener Agent
I deployed the Screener Agent. Why has it not opened any position? `Osprey V2 High Volume 5M (Selective)` is selective by design. It waits for higher confidence entries instead of forcing constant positions. Choose `Osprey Edge` for a balance between opportunity and risk. If you want broader opportunity coverage, `Osprey V2 High Volume 5M (Degen)` targets more entries. Higher frequency comes with tradeoffs: more entries, more activity, and higher risk.
## Related Pages * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) * [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent) * [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) * [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Screener Agent Position Management Automations](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Screener Agent Exit Settings Automations](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) ## More Questions? * Join our Discord for questions and discussions on HawkFi: # Osprey Trading Agent 24/7 autonomous trenching Catching a token opportunity is only half the job. You still need to size the entry, manage the trade, watch the risk, and exit on time. If you have traded from Axiom, GMGN, or Photon, you know how quickly a token screener becomes a firehose. New pairs, migrations, memes, and short-lived activity compete for attention every second. Most screener feeds can feel like 99% noise. The hard part is finding the small amount of signal worth acting on.
A dense token screener feed showing new pairs, final-stretch tokens, and migrated tokens

Status quo: new pairs, migrations, and short-lived activity compete for attention in a dense screener feed.

Osprey is built for the signal side of that workflow. It screens continuously, applies the selected model and your personalized rules, then sends eligible opportunities into the Agent's trading checks. Osprey Trading Agent is built for direct token trading. It can turn an eligible Osprey signal into a token trade using the entry size, total allocation, filters, re-entry behavior, and exit rules you customize in advance. {% hint style="success" %} Osprey Trading Agent is for token trading. It does not open LP positions like Screener Agent or manage live bid and ask quotes like Market Making Agent. {% endhint %} ## What is the Osprey Trading Agent? Osprey Trading Agent is a HawkFi Agent for users who want Osprey to watch for opportunities 24/7 and trade selected tokens within personalized boundaries. When a signal matches the selected Osprey model and filters, the agent can buy the selected token using its trading balance. The configured take profit, stop loss, or maximum hold can sell the full position back to the agent's trading balance. You can also request a manual exit or close the agent. {% hint style="info" %} Osprey Trading Agent is available from the [New Agent page](https://www.hawkfi.ag/agents/new). Choose `Osprey Trading Agent` after connecting and authenticating the wallet that will own the agent. {% endhint %} ## Quick start The basic journey is straightforward: | Step | What to do | | ----------------------------- | ------------------------------------------------------------------------------------------------------ | | 1. Choose the Agent | Open the New Agent page and select `Osprey Trading Agent`. | | 2. Set the capital boundaries | Choose `SOL per entry`, `Maximum agent allocation`, and `Maximum open trades`. | | 3. Choose how Osprey screens | Select `Osprey High Volume 5m Selective`, `Osprey High Volume 5m Degen`, or `Osprey Edge`. | | 4. Set trade rules | Configure market-cap boundaries, optional filters, re-entry behavior, and full-position exit controls. | | 5. Review and activate | Review the setup, select `Create Agent and Deposit`, and approve the funding transaction. | | 6. Monitor trades | Follow Agent status, open trades, and closed trades from HawkFi Agents. | The full walkthrough below shows the same journey with the exact controls and screenshots. ### Choose an Osprey model Osprey Trading Agent offers three screening models. Selective remains the default. | Model | Entry approach | | --------------------------------- | ----------------------------------------------------------------------------------------------------- | | `Osprey High Volume 5m Selective` | Fewer, highest-confidence entries. | | `Osprey High Volume 5m Degen` | Broader coverage, more entries, and higher risk. | | `Osprey Edge` | Balanced opportunity and risk. It uses ML-powered signal ranking to guide entry selection and sizing. | When you select `Osprey Edge`, `TARGET ENTRIES PER DAY` sets a rolling 24-hour cap. This Edge-only control is separate from `Adaptive sizing strength`, which controls whether an eligible entry can be smaller than `SOL per entry`. ## Why use Osprey Trading Agent Use Osprey Trading Agent when you want a repeatable token-trading workflow without manually watching every signal and rebuilding the entry and exit plan each time. | Benefit | What it means | | -------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | | Continuous opportunity screening | Osprey watches for eligible opportunities 24/7. Signals must match the selected model and filters before the agent considers them for entry. | | Personalized capital boundaries | You define the entry size, total allocation, and maximum number of open trades before activation. | | Custom filters and exits | You choose Selective, Degen, or `Osprey Edge`, plus market-cap boundaries, optional token filters, re-entry behavior, and full-position exit controls. | | Repeatable trade rules | The agent uses the configured screening, entry, re-entry, and full-position exit controls when evaluating and managing eligible opportunities. | | Monitoring in one place | HawkFi Agents shows Agent status alongside open and closed token trades. | ## Two ways to manage Osprey trades Osprey gives you two ways to manage a trade: Autopilot and Copilot. Both automate eligible entries. The difference is how you manage the full-position exit. | Approach | How it works | Example setup | | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Autopilot | Osprey enters the trade, then exits the full position based on your configured `Set take profit` and `Set stop loss` targets. | Current-default example: `Set take profit` at `+16%` and `Set stop loss` at `-40%`. Osprey exits when either target is reached. | | Copilot | Osprey enters the trade, then you decide whether to use `EXIT` or keep holding based on conviction. Your configured `Set take profit` and `Set stop loss` targets remain active. | Use `+160%` for `Set take profit` and `-80%` for `Set stop loss`. These wider targets give the trade more room to move, but require active monitoring. You can still manually exit the trade at any time if your conviction changes. | {% hint style="info" %} `Set take profit` and `Set stop loss` remain required for both approaches. These examples show how each approach can be configured. They are not recommended exit percentages, and neither approach guarantees a profitable exit or exact execution price. {% endhint %} ## How Osprey Trading Agent works Your settings define what can qualify, how much capital the Agent can deploy, and how a full-position exit is handled. | Building block | What it controls | | --------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Entry Settings | Sets the agent name, entry size through `SOL per entry`, total allocation, maximum open trades, Osprey model, entry slippage, market-cap range, adaptive sizing, re-entry behavior, and optional token filters. | | Osprey screening | Uses high-volume token signals from the selected Osprey model and the configured filters to determine whether a signal is eligible for this agent. | | Trade entry | Buys the selected token from the agent's trading balance after an eligible signal passes the configured limits. | | Exit Settings | Requires full-position take profit and stop loss, then applies exit slippage and an optional maximum hold. | | Funding and lifecycle | Creates the agent, deposits its configured allocation, activates it after funding succeeds, and exposes edit, exit, pause, and close controls from the Agents interface. | {% hint style="info" %} The app's `Agents Fund` is the shared SOL reserve used for temporary account rent. Returned rent goes back to `Agents Fund` when a temporary token account closes. This reserve is separate from the Osprey Trading Agent's isolated WSOL trading principal, which funds entries and receives exit proceeds. {% endhint %} {% hint style="success" icon="circle-info" %} `Adaptive sizing strength` can reduce an eligible entry below `SOL per entry` only when adaptive sizing is active at the deployment level and a valid downside-sizing score is available. If the scorer or deployment mode is off, or no valid score is available, the agent uses the configured `SOL per entry` as its static base size. The allocation and open-trade limits still apply in both cases. {% endhint %} {% hint style="warning" icon="circle-info" %} Osprey Trading Agent opens token trades, not LP positions. Direct token exposure can lose value quickly, and configured exits do not guarantee an exact execution price. {% endhint %} {% hint style="info" %} Pausing an Osprey Trading Agent prevents new entries. Take profit, stop loss, maximum hold, manual exits, and closure exits remain active for open trades. {% endhint %} ## What you can do today Osprey can find eligible opportunities, enter trades automatically, follow your take-profit and stop-loss settings, and show your open and closed trades in one place. You can also manually exit any open trade. ## What's next We're planning more ways to help you follow, manage, and share your Osprey trades. These features are not live yet: * Telegram notifications when Osprey opens a trade * Entry market cap compared with all-time-high market cap, so you can see how far a token has moved and decide whether to hold or exit * Shareable PNL cards for Osprey Trading Agent trades * A live Osprey signal feed showing win rates and profit multipliers * V2 Agent Terminal ## How to deploy Osprey Trading Agent Use this simplified walkthrough to create an Osprey Trading Agent. {% hint style="info" %} The supplied figures show `Edit Agent`. The same settings appear during creation, where the final action is `Create Agent and Deposit`. Editing an existing agent ends with `Save changes`. {% endhint %} {% stepper %} {% step %} #### Visit HawkFi Agents and connect your wallet. [Open HawkFi Agents](https://www.hawkfi.ag/agents), connect the wallet that will own the agent, and complete HawkFi account setup if prompted. {% endstep %} {% step %} #### Open New Agent and select Osprey Trading Agent. Select `Osprey Trading Agent` from the three Agent options. The setup uses two sections: `Entry Settings` and `Exit Settings`. {% endstep %} {% step %} #### Configure Entry Settings.
Osprey Trading Agent sizing and model controls

Set the agent name, entry size, total allocation, open-trade limit, Osprey model, and entry slippage.

Set `Agent Name`, `SOL per entry`, `Maximum agent allocation`, and `Maximum open trades`. Choose `Osprey High Volume 5m Selective`, `Osprey High Volume 5m Degen`, or `Osprey Edge`, then review `ENTRY MAX SLIPPAGE`. If you choose `Osprey Edge`, also review `TARGET ENTRIES PER DAY`. {% endstep %} {% step %} #### Set the risk boundary and entry controls.
Osprey Trading Agent market cap, adaptive sizing, re-entry, and filter controls

Configure market cap, adaptive sizing, re-entry behavior, and optional filters.

Set at least one `MARKET CAP RANGE` boundary. Review `Adaptive sizing strength` and `No re-entry`, then use `ADD FILTER` if the agent needs additional token-level limits. {% endstep %} {% step %} #### Configure Exit Settings.
Osprey Trading Agent take profit, stop loss, exit slippage, and maximum hold controls

Configure fixed full-position exits and review the setup before saving or creating the agent.

Set both `Set stop loss` and `Set take profit`. Review `Exit slippage` and the optional `Maximum hold`, which requests an exit at the next evaluation after the configured number of minutes from confirmed entry. {% endstep %} {% step %} #### Review, create, and deposit. Select `Review from the top`, confirm every control, then select `Create Agent and Deposit`. Approve the connected-wallet transaction that funds the agent allocation. After funding and activation succeed, HawkFi reports `Osprey Trading Agent funded and active` and the agent waits for the next eligible Osprey signal. {% endstep %} {% endstepper %} ## FAQs for Osprey Trading Agent
Why has my Osprey Trading Agent not opened a trade? The agent waits for an eligible signal from the selected Osprey model. A signal can also be skipped when it does not match the configured filters, the agent has reached `Maximum open trades`, the next entry would exceed `Maximum agent allocation`, or the token is blocked by the current re-entry rule.
What happens when I manually exit a trade? The full current token balance is swapped back to the agent's WSOL account using the configured `Exit slippage`. The exit fee is deducted from the gross WSOL output before net proceeds reach the isolated WSOL account. The empty token account is then closed and its rent is returned to `Agents Fund`.
## Fees
Detailed table Each entry and exit swap includes a `1%` execution fee. On entry, the fee is deducted from the gross WSOL input, so `99%` of that input is routed into the token swap. On exit, the fee is deducted from the gross WSOL output before net proceeds are credited to the agent's isolated WSOL account. Network activity and account setup can also require SOL. Review the connected wallet and agent balance before creating, funding, exiting, or closing an agent. See [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) for the shared fee and risk reference.
## Related Pages * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) * [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent) * [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) * [Screener Agent with Osprey](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) * [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) ## More Questions? * Join our Discord for questions and discussions on HawkFi: # Tune Your Osprey Trading Agent Settings Review Osprey Trading Agent settings and monitor balances, trades, and manual exits. **As of July 2026:** The values below are the verified defaults and validation ranges for a newly selected Osprey Trading Agent. They can change as the product evolves, and existing agents keep their saved settings when opened for editing. | Setting | Current default | Supported behavior | | -------------------------- | --------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `SOL per entry` | `0.1 SOL` | Accepts `0.001` to `1 SOL`. This is the maximum base size for one entry. | | `Maximum agent allocation` | `0.3 SOL` | Must cover the configured entry size across the allowed open trades. | | `Maximum open trades` | `3` | Accepts `1` to `10` concurrent trades. | | `OSPREY TRADING AGENT` | `Osprey High Volume 5m Selective` | Select `Osprey High Volume 5m Selective`, `Osprey High Volume 5m Degen`, or `Osprey Edge`. | | `TARGET ENTRIES PER DAY` | `10` for `Osprey Edge` | Available only when `Osprey Edge` is selected. Accepts `1` to `40` and sets a rolling 24-hour cap. The Agent may enter fewer trades when fewer calls qualify. It does not change `SOL per entry` or guarantee a number of trades. | | `ENTRY MAX SLIPPAGE` | `3%` | Accepts `0.01%` to `5%`. | | `MARKET CAP RANGE` | Minimum `100,000 USD`; no maximum | At least one non-negative boundary is required. The minimum must be lower than the maximum when both are set. | | `Adaptive sizing strength` | `100%` | Accepts blank or `0%` for fixed sizing, or `1%` to `100%` for partial to full adaptive sizing. A reduction occurs only when deployment-level adaptive sizing is active and a valid score is available; otherwise the configured `SOL per entry` remains the static base size. | | `No re-entry` | Enabled | Prevents the agent from entering the same token mint more than once. If disabled, a re-entry cooldown can be set. | | `Set stop loss` | `-40%` | Required for Osprey Trading Agent and applies to the full position. | | `Set take profit` | `+16%` | Required for Osprey Trading Agent and applies to the full position. | | `Exit slippage` | `3%` | Accepts `0.01%` to `5%`. | | `Maximum hold` | `480 minutes` | Optional. Accepts `1` to `525,600` minutes or blank for no limit. | {% hint style="info" %} `TARGET ENTRIES PER DAY` limits how many entries `Osprey Edge` can make in a rolling 24-hour period. `Adaptive sizing strength` is separate: it controls whether an eligible entry can be reduced below `SOL per entry`. Changing one does not change the other. {% endhint %} ### Optional Entry Settings filters | Filter | What it controls | | ----------------------- | --------------------------------------------- | | `Token liquidity` | Filters signals by token-level liquidity. | | `Age (hours)` | Filters signals by token age. | | `Jupiter organic score` | Filters signals by Jupiter Organic Score. | | `5m volume` | Filters signals by recent five-minute volume. | | `Fees` | Filters signals by fee activity. | ## Monitoring balances and trades after launch Once the agent is live, HawkFi Agents keeps the Agent status and trade history in one place. Use the Agents table for the overall Agent. Use Open Positions and Closed Positions to follow individual trades: | Surface | What it shows | | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Agents table | Agent status, portfolio balance, `HODL`, `PROFIT`, configuration actions, and a shortcut to the agent's positions. The portfolio balance values the agent's WSOL and open token accounts in USD or SOL. | | Open Positions | Token, age and agent name, current token balance, entry price, asset, `UNREALIZED PNL`, entry transaction, and `EXIT`. | | Closed Positions | Token, trade age, agent name, `REALIZED PNL`, closure time, and entry and exit transaction links. | Select `EXIT` to review a manual full-position exit. `Approve & Exit` authorizes the current token balance to be swapped back to the agent's WSOL account. The empty token account is then closed and its rent is returned to `Agents Fund`. # HawkFi Laboratory Experiment with MM and LP agent configurations against HODL and passive benchmarks before deploying real capital. ## What is HawkFi Laboratory HawkFi Laboratory is the research layer of the HawkFi Agent Terminal. Use it to test MM and LP strategies, HawkFi Models, and agent configurations before deploying real capital. Laboratory turns the manifesto into a practical workflow: choose an asset, choose a market window, simulate a strategy, compare it against HODL and passive benchmarks, then refine the model or agent configuration before live execution. ## Why use Laboratory? {% stepper %} {% step %} ### Test Models Backtest existing HawkFi Models, Market Making configurations, or custom LP setups on real historical pool data before deploying capital. {% endstep %} {% step %} ### Compare and optimize Compare results against HODL and passive benchmarks, or use Optimize to find a model that fits the selected asset and regime. {% endstep %} {% step %} ### Execute your winning formula into a model Refine the setup, pick the model or agent configuration that fits the selected market, then use it as your starting point for live execution. {% endstep %} {% endstepper %} ### From backtest to execution Once you find a Market Making or Liquidity Providing setup that fits your pool, market view, and risk style, use it as your starting point for real execution in the Agent Terminal. [Move from Backtest to Live](/whitepaper/hawkfi-laboratory/move-from-backtest-to-live) explains the checks to make before turning a Laboratory result into a live setup. ## Laboratory modes HawkFi Laboratory currently has two modes. | Mode | Use this when you want to | What you'll get | | ------------------------------------------------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [Liquidity Providing](/whitepaper/hawkfi-laboratory/liquidity-providing) | Backtest DLMM liquidity strategies, [HawkFi models](/whitepaper/models-and-automations-library/hawkfi-models), [automations](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models), and custom model setups against passive LP and hold benchmarks. | Helps you prepare setups for the core [HawkFi DApp](https://www.hawkfi.ag/), or refine [execution models](/whitepaper/models-and-automations-library/hawkfi-models) for [HawkFi Screener Agent](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | | [Market Making](/whitepaper/hawkfi-laboratory/market-making) | Backtest Dynamic Limit Order or Market Making Agent configurations before creating a [HawkFi Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | Helps you prepare and refine your Market Making Agent's [execution models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models), [advanced settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings), and New Agent setup. | {% hint style="info" %} Backtests do not predict the future, but HawkFi Laboratory gives you a place to keep experimenting, refining, and comparing until you find the model or agent configuration you want to deploy. {% endhint %} ## Practical simulating tips * Test the same pool, same time window, and same deposit amount when comparing setups. * Do not judge a model or strategy from final PnL alone. * Use pool behavior to guide strategy choice. Trending, ranging, high fee, and low fee pools can favor different setups. * Treat a backtest as research, not a promise. * Recheck live market conditions before deploying capital. ## Related Pages * [Test a Market Making Setup](/whitepaper/hawkfi-laboratory/market-making) * [Test an LP Setup](/whitepaper/hawkfi-laboratory/liquidity-providing) * [Move from Backtest to Live](/whitepaper/hawkfi-laboratory/move-from-backtest-to-live) ## More Questions? * Join our Discord for questions and discussion: # Market Making Backtest quote placement, quote refresh, fills, inventory behavior, spread settings, and markout performance on real historical DLMM pool data. Market Making Mode is the HawkFi Laboratory mode for experimenting with Dynamic Limit Order and Market Making Agent configurations before live execution. ## What is Market Making Mode? In Market Making Mode, Laboratory experiments with LP ranges and liquidity strategies. In Market Making Mode, Laboratory experiments with [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma)'s Dynamic Limit Order style behavior: buy quotes below price, sell quotes above price, inventory management, quote replacement, quote widening, and fill quality. ## Metrics of Market Making Mode ### Result Metrics The top result cards summarize performance and risk. | Metric | What it means | | ------------ | --------------------------------------------------------------------------------------------- | | Net PnL | The simulated Market Making setup PnL for the selected window. | | Win Rate | The percentage of positive markouts. The UI can also show markout counts beside the win rate. | | Pair HODL | The result from holding the pool pair instead of running the simulated configuration. | | Fees | Fees or fee-related value shown for the simulation. | | Max Drawdown | The largest peak decline during the backtest. | {% hint style="info" %} Use `Percentage` or `Absolute` to switch how results are displayed. {% endhint %} ### Equity Curve Metrics The Equity Curve shows how performance changed over time. | Line | What it means | | ----------------- | --------------------------------------------------------------------------- | | Simulated PnL | The performance of the Market Making configuration being simulated. | | Pair HODL PnL | The result from holding the pool pair instead of running the configuration. | | Single token HODL | The result from holding one side of the pair, when available. | | Cumulative Fees | The fees accumulated by the simulated setup, when enabled. | Use this chart to see whether the configuration created steady markout over time or relied on a few large moves. ### Price & Range Chart Price & Range shows pool price, quote range, and rebalance markers. | Line or label | What it shows | | ------------- | ---------------------------------------------------------------------------- | | Price | The pool price through the backtest window. | | Range high | The upper side of the simulated quote or range area. | | Range low | The lower side of the simulated quote or range area. | | Rebalance | Markers showing where the configuration refreshed quotes or rebalanced. | | Rebalances | The total number of quote refresh or rebalance events during the simulation. | Use this panel to understand how often the configuration moved with price. ### TVL Breakdown TVL Breakdown shows the simulated token composition over time. | Example for a simulated SOL-USDC pool | What it means | | ------------------------------------- | ------------------------------------------------------------- | | SOL TVL | The simulated SOL value held by the configuration over time. | | USDC TVL | The simulated USDC value held by the configuration over time. | Use TVL Breakdown to inspect inventory drift. A Market Making setup can show strong markout while ending with a different token mix, so this chart gives more context than PnL alone. ### Market Making Diagnostics Market Making Diagnostics is the deeper readout for quote quality, fills, inventory, cost, and markout. | Diagnostic | What it means | | ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Fills | Total simulated fills and bid or ask side split. | | Quote Updates | How many times quotes were updated or refreshed. High activity is useful only if it improves edge. | | Filled Turnover | How much turnover the simulated quotes created relative to starting capital. | | LO Fees | Limit Order fee value shown by the simulation. | | Quote Update Cost | Modeled operational cost for quote updates. | | Final Inventory | Final inventory bias after the simulation. Use this to check whether PnL came with unwanted inventory drift. | | Open Order Notional | Open order notional usage in the simulated configuration. | | Spread Bins | Quote spread distance relative to the maximum spread setting. | | Stoikov offset | The latest simulated shift applied to the quote center, measured in DLMM bins. A value of `0 bins` means no Stoikov shift is active at that point. | | Fill Model | Shows how Laboratory determines whether a simulated quote fills, including the candle price range, required fill-through distance, and maximum fills allowed per candle. | | Suppressed Fills | The number of potential fills excluded by the simulation's fill limits. Suppressed fills do not affect simulated PnL, inventory, turnover, or equity. | | Peak Fill Density | The highest number of simulated fills recorded within rolling 30-minute, 60-minute, 4-hour, and 24-hour periods. | | Fills / Day | The average number of simulated fills per day during the selected backtest window. | ### Markout Horizons Markout horizons show whether fills were favorable after different time windows. | Markout horizon | What it means | | --------------- | -------------------------------------------------------- | | 5m | Mean net markout five minutes after fills. | | 15m | Mean net markout fifteen minutes after fills. | | 30m | Mean net markout thirty minutes after fills. | | 60m | Mean net markout sixty minutes after fills. | | 120m | Mean net markout one hundred twenty minutes after fills. | Positive markout means fills were favorable over that horizon in the simulation. Negative markout can suggest the quotes were getting picked off or filled before adverse price movement. ### Simulation Summary Under the charts, Laboratory shows a compact summary. | Field | What it means | | -------------- | ---------------------------------------------------------------------- | | Window | The exact historical period used for the backtest. | | Time in Range | The percentage of the selected window covered by the simulation state. | | Rebalances | The number of quote or range refresh events shown by the simulation. | | Liquidity Mode | The internal simulation mode used to process the backtest. | ### Liquidity Replay Animation Liquidity Replay Animation lets you inspect the simulated state frame by frame. | Field | What it means | | ---------- | ---------------------------------------------------- | | Frame | The current replay frame out of the full simulation. | | Timestamp | The historical time represented by the frame. | | Active Bin | The active DLMM bin at that moment. | | Range | The simulated quote or range area at that moment. | | Price | The pool price at that moment. | | Event | The current replay event count or state. | Use replay when you want to inspect how the configuration moved through time instead of only reading the result cards. ## How to run a Market Making Mode backtest {% embed url="" %} Use this simplified walkthrough to experiment with a Dynamic Limit Order setup in HawkFi Laboratory. {% stepper %} {% step %} #### Select Market Making Mode Use the `Mode` selector and choose Market Making. {% endstep %} {% step %} #### Paste a pool address Paste the DLMM pool address into `Pool Address`. You can test examples such as SOL-USDC, cbBTC, whETH, ZEC, JUP, JLP, MET, JTO, or HYPE. Thinner examples such as CARDS, PUMP, or PUMPCADE should be treated as higher-risk experiments and checked carefully against fill quality and inventory drift. When the pool loads, Laboratory displays the pair, base fee, and bin step. | Pool detail | Example shown | | ------------- | ------------- | | Pair | SOL USDC | | Base fee | 0.04% | | Bin step | 4 | | {% endstep %} | | {% step %} #### Set Start and End Use `Start` and `End` to choose the historical backtest window. Use this when you want to experiment with a specific market period, such as a launch window, range period, volatility spike, or recent pool behavior. For eligible pools, `Event-Driven (BETA)` uses available event history, may adjust the date range automatically, and refreshes optimization results hourly. {% endstep %} {% step %} #### Set Initial USDC Use `Initial USDC` to set the starting value used for the simulated configuration. {% endstep %} {% step %} #### Choose an Execution Model Select the `Execution Model` you want to experiment with. Execution Models set how a Market Making Agent starts placing quotes. Choose a model based on the pool and asset category, then adjust settings if you want a different balance between fill opportunity and protection. | Execution Model | Use it for | Starting behavior | | ------------------- | -------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | | `SOL Wide` | SOL-USDC when you prefer more distance from the current price. | Starts with wider quote placement and a more defensive fill posture. | | `SOL Tight` | SOL-USDC when you want quotes closer to price. | Starts with tighter quote placement for more fill opportunity, with greater adverse-selection risk. | | `Blue Chip General` | Non-SOL assets with a market cap of $1B or more. | Uses quote distances that adjust to the selected pool’s DLMM bin step, so the model keeps a similar quote posture across blue-chip pools. | | `Mid-Cap` | Assets with a market cap from $100M to $1B. | Starts with a balanced posture for active pools with less depth than blue chips. | | `Small-Cap` | Assets with a market cap from $10M to $100M. | Starts more defensively to account for thinner liquidity and faster inventory movement. | | `Micro-Cap` | Assets with a market cap below $10M. | Starts with the most defensive defaults for sparse and more volatile liquidity. | Market cap is a starting guide for the non-SOL models. Pool liquidity, volume, fee tier, and current price behavior still matter. Use `Reset parameters to defaults` when you want to return the controls to the selected Execution Model defaults. Want to dive more about Execution Models? See [Execution Models here](/whitepaper/market-making-agent/market-making-agents-mma/execution-models). {% endstep %} {% step %} #### Adjust primary controls Use the primary controls to change inventory usage, live order count, inventory split, replace interval, open order notional, and spread factor. | UI field | What it controls | | ------------------------- | -------------------------------------------------------------------------------------------------------------------------------- | | Inventory Utilization | How much of the available capital can sit in live quotes. Higher usage can create more fill opportunity and more inventory risk. | | Live Orders | How many live bid and ask orders the configuration keeps open. More orders create a wider quote ladder. | | Inventory Split | The target balance between base and quote inventory. More base supports asks. More quote supports bids. | | Unfilled Replace Interval | How long stale unfilled quotes can remain before being replaced. Faster refresh reacts faster but creates more activity. | | Max Open Order Notional | The maximum open order notional used by the simulated configuration. | | Spread Factor | Scales quote distance. Lower values are tighter and more fill-seeking. Higher values are wider and more selective. | | {% endstep %} | | {% step %} #### Optional: Open Advanced Settings Advanced Settings are for users who want more control over how cautious, aggressive, or selective the configuration should be when placing orders. Most users should start with an Execution Model default, then experiment in Laboratory before making a live configuration more aggressive. The current Laboratory UI can show these Advanced Settings: | UI field | What it controls | | ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- | | Adaptive Spread | Allows quote placement to adjust as market conditions change. | | EV Gate | Turns expected-value gating on or off before placing size. | | Requote on Fill | Refreshes quote placement after a fill. | | Slippage BPS | Sets the slippage assumption in basis points. | | Spread Bins | Sets the starting quote distance from price in DLMM bins. | | Level Spacing Bins | Controls spacing between quote levels when using multiple bids and asks. | | Stoikov gamma (experimental) | Shifts the bid and ask quote center away from excess inventory. `Off` preserves the existing quote center; higher values create a stronger shift. | `Stoikov gamma (experimental)` ranges from `Off` to `1.0` and is off by default. It changes quote prices, while inventory skew changes side sizes. Use candle simulation for positive gamma values. `Event-Driven (BETA)` currently supports gamma `0` only. These settings map into the same configuration families used by the [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma): | Setting group | What it controls | | ------------- | ------------------------------------------------------------------------------------------ | | Placement | Where quotes sit around price and how they respond when conditions change. | | Signals | Whether current price action is clean enough to quote or should be treated more carefully. | | Momentum | Protection from one-sided or fast-moving price action. | | EV Gate | Whether the configuration requires more expected edge before taking risk. | | Sizing | How much size the configuration can place on each side. | | Requote | When old quotes should be replaced. | Want to learn more about Market Making Agent Advanced Settings? See [Advanced Settings here](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings). {% endstep %} {% step %} #### Optimize! Click `Optimize` when you want Laboratory to search across candidate Market Making configurations for the selected pool, window, and deposit amount. There are three Optimize options. | Optimize option | What it means | | --------------- | ------------------------------------------------------------------------------------------------------------------------- | | Light | Searches a faster set of candidate configurations. | | Deep | Searches a wider set of candidate configurations and can take longer. | | Ultra Deep | Searches the widest candidate set. This option requires at least $500 total agent balance for Market Making optimization. | Optimization can evaluate Stoikov gamma values of `0`, `0.5`, and `1` alongside the other candidate settings. Open `Advanced` in the optimization modal to adjust the exploration percentage for each optimize depth. Exploration controls how much of the fixed optimization budget is reserved for newer or less common candidate strategies before Laboratory runs the backtests. | Exploration control | Default | | -------------------------- | ------- | | `Light Exploration %` | 20% | | `Deep Exploration %` | 25% | | `Ultra Deep Exploration %` | 35% | A higher exploration percentage tests more uncommon candidate setups. A lower exploration percentage keeps more of the budget focused on known-good candidate regions. The control only changes the candidate mix for the current optimization request; it does not change saved Execution Model settings or live Market Making Agent execution. {% endstep %} {% step %} #### Run Backtest Click `Run Backtest`. Laboratory simulates the selected Market Making configuration over the selected pool and time window. After a backtest, click `Create Market Making Agent`, name the agent, add SOL, then select `Fund and deploy agent`. Under `Strategy actions`, `Save Model` appears before `Optimize`. Use `Save Model` when you want to preserve a configuration for later use, when that workflow is supported. {% endstep %} {% endstepper %} ## Market Making Mode tips * Start with the Execution Model that matches the pool quality and depth. * Use Laboratory before making a live Market Making Agent configuration more aggressive. * Lower Spread Factor can increase fill opportunity, but can also increase toxic fill risk. * Higher Inventory Utilization can create more opportunity and more inventory risk. * Review Win Rate and markout diagnostics before trusting Net PnL. * Watch Final Inventory so a good PnL result does not hide unwanted inventory drift. * Use Advanced Settings only when you understand the tradeoff being changed. ## Related Pages * [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) * [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) * [Market Making Agent Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) * [Market Making Agent Advanced Settings](/whitepaper/market-making-agent/market-making-agents-mma/advanced-settings) ## More Questions? * Join our Discord for questions and discussions on HawkFi: # Liquidity Providing Backtest DLMM liquidity strategies, HawkFi models, and automations against passive LP benchmarks. ## Liquidity mode Liquidity Mode is the HawkFi Laboratory mode for LP strategy simulation.\ \ Paste a pool address, select a time window, configure a strategy, run the backtest, and study the result before deploying real capital. ## Metrics of Liquidity Mode ### Result Metrics The Result Metrics of HawkFi Laboratory summarize performance and risk. | Metric | What it means | | ------------ | -------------------------------------------------------------------------------- | | Net PnL | The simulated HawkFi strategy PnL for the selected window. | | Manual LP | The passive 69 spot bins for the same pool and window. | | Pair HODL | The result from holding the pool pair instead of running the simulated strategy. | | Fees | Fees earned by the simulated strategy. | | Max Drawdown | The largest peak decline during the backtest. | {% hint style="info" %} Use `Percentage` or `Absolute` to switch how results are displayed. {% endhint %} ### Equity Curve Metrics The Equity Curve of HawkFi Laboratory shows how performance changed over time.
LineWhat it means
Simulated PnLThe performance of the HawkFi model or custom setup being simulated.
Manual PnLThe passive LP benchmark over the same pool and window.
Pair HODL PnLThe result from holding the pool pair instead of running a strategy.
Single token HODLThe result from holding one side of the pair, when available.
Cumulative FeesThe fees accumulated by the simulated setup, when enabled.
Use this chart to see when outperformance appeared, when drawdown happened, and whether the final result came from a steady edge or a late move. ### Price & Range Chart Price & Range chart of HawkFi Laboratory shows pool price relative to the simulated strategy range. | Line or label | What it shows | | ------------- | ------------------------------------------------------------------------ | | Price | The pool price through the backtest window. | | Range high | The upper maximum range of the simulated range. | | Range low | The lower minimum range of the simulated range. | | Rebalance | Markers showing where the strategy rebalanced, when rebalances occurred. | | Rebalances | The total number of rebalances during the simulation. | Use this panel to understand whether the strategy stayed positioned around price or spent too much time away from the active market. ### TVL Breakdown TVL Breakdown of HawkFi Laboratory shows the simulated token composition over time. |

Example for a simulated

(SOL-USDC pool)

| What it means | | ---------------------------------------------------- | -------------------------------------------------------- | | SOL TVL | The simulated SOL value held by the position over time. | | USDC TVL | The simulated USDC value held by the position over time. | Use TVL Breakdown to inspect how inventory shifted through the range. A strategy can earn fees while ending with a different token mix, so this chart gives more context than PnL alone. ### Simulation summary Under the charts, Laboratory shows a compact summary. | Field | What it means | | -------------- | -------------------------------------------------------------------------------- | | Window | The exact historical period used for the backtest. | | Time in Range | The percentage of the selected window where the simulated position was in range. | | Rebalances | The number of times the strategy rebalanced during the simulation. | | Liquidity Mode | The internal simulation mode used to process liquidity behavior. | ### Liquidity Replay Animation Liquidity Replay Animation lets you inspect the simulated position frame by frame. | Field | What it means | | ---------- | ---------------------------------------------------- | | Frame | The current replay frame out of the full simulation. | | Timestamp | The historical time represented by the frame. | | Active Bin | The active DLMM bin at that moment. | | Range | The simulated position range at that moment. | | Price | The pool price at that moment. | | Event | The current replay event count or state. | The replay bars show token distribution across bins. Use this panel when you want to understand how the strategy behaved inside the range instead of only reading final PnL. ## How to run a Liquidity Mode backtest Use this simplified walkthrough to experiment with a DLMM liquidity setup in HawkFi Laboratory. {% stepper %} {% step %} #### Select Liquidity Mode
Use the `Mode` selector and choose `Liquidity`. {% endstep %} {% step %} #### Paste a pool address
Paste the DLMM pool address into `Pool Address`. When the pool loads, Laboratory displays the pair, base fee, and bin step. In the SOL USDC screenshot, the pool reflects: | Pool detail | Example shown | | ------------- | ------------- | | Pair | SOL USDC | | Base fee | 0.04% | | Bin step | 4 | | {% endstep %} | | {% step %} #### Set Start and End
Use `Start` and `End` to choose the historical backtest window. The selected period controls which pool data Laboratory uses for the simulation. The date picker lets you select the calendar date and time. Use this when you want to test a specific market period, such as a launch window, drawdown, recovery, or recent pool behavior. {% endstep %} {% step %} #### Set Initial USDC
Use `Initial USDC` to set the starting quote amount. For SOL quote pools, this is the amount of TVL in USDC used in the simulated position.\ \ For SOL quote pools, this is the amount of TVL in USDC used in the simulated position.\ \ For other quote pools, this is the amount of TVL in USDC used in the simulated position. {% endstep %} {% step %} #### Optimize!
Click `Optimize` when you want Laboratory to search for stronger strategy configurations across the selected pool, time window, and deposit amount. Under `Strategy actions`, `Save Model` appears before `Optimize`. There are two Optimize options | Optimize options | What it means | | ---------------- | -------------------------------------------------------------------------------------------------------- | | Light | It optimizes across 62 curated strategies proven to perform well on SOL/USDC. Finishes in a few seconds. | | Deep | Optimizes across \~212 strategies. Takes noticeably longer but searches a much wider space. | | {% endstep %} | | {% step %} #### Optional: Configure Strategy
Click `Configure` to select or customize the liquidity setup. You can either create a custom setup from scratch or start from an existing HawkFi model. {% stepper %} {% step %} ### Option 1: Create from scratch
Use `Create from scratch` when you want to build the setup manually.
SettingWhat it controls
Initial Deposit PreferencesChoose the starting liquidity shape, such as Spot, Curve, Bid-ask, or Hybrid.
Single-sided quote tokenStart the position using only the quote token, when enabled.
Position Width BasisChoose whether the range width is set by bin count or price percentage.
Below the Price / Above the PriceSet how many bins the position uses below and above the current price.
Total Number of BinsThe total simulated position width.
{% endstep %} {% step %} ### Option 2: Customize an existing model
Use `Customize an existing model` when you want to start from a HawkFi model, then adjust it for the pool and market window you are experimenting with. Want to learn more about HawkFi Models? See [HawkFi Models here.](/whitepaper/models-and-automations-library/hawkfi-models) {% endstep %} {% endstepper %} {% endstep %} {% step %} #### Run Backtest
Click `Run Backtest`. Laboratory simulates the selected strategy over the selected pool and time window.
`Execute Strategy` appears below the `Initial USDC` and `Strategy actions` row. Run and review the backtest before using it to deploy the setup. {% endstep %} {% endstepper %} ## Liquidity Mode tips * Compare strategies using the same pool, same window, and same deposit. * Read Net PnL beside Manual LP and Pair HODL. * Check Max Drawdown before judging a backtest as good. * Use Price and Range to see whether the range matched the market. * Use TVL Breakdown to understand inventory changes. * Use Liquidity Replay to inspect how the position behaved through time. ### More Questions? * Join our Discord for questions and discussion: # Move from Backtest to Live Turn a HawkFi Laboratory result into a more deliberate live setup without treating the backtest as a promise. HawkFi Laboratory helps you test liquidity behavior, model settings, and Market Making Agent mechanics before using live capital. A backtest shows how a setup behaved during the selected historical period. It does not predict future returns. ## Before you deploy Keep the pool, historical window, and deposit amount consistent while comparing configurations. This makes it easier to understand what changed. | If you tested | Review before going live | | ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | Market Making Agent | Net PnL, Pair HODL, Max Drawdown, win rate, markout horizons, fills, quote updates, final inventory, open-order notional, and quote update cost. | | Liquidity Providing | Net PnL, Manual LP, Pair HODL, fees, Max Drawdown, time in range, rebalances, and TVL breakdown. | ## Move from research to live execution {% stepper %} {% step %} ### Explain why the setup fits the market Write down the pool behavior you tested and why the selected execution model, range, or settings matched that period. {% endstep %} {% step %} ### Check where the result came from Use the equity curve and replay instead of judging only the final PnL. Check whether the result was steady, depended on one late move, or came with inventory drift and drawdown you would not accept live. {% endstep %} {% step %} ### Change one input at a time If the setup needs improvement, change one decision and run the backtest again. Keep the pool, window, and deposit consistent so the comparison remains useful. {% endstep %} {% step %} ### Choose the matching live path * For Market Making Mode, click `Create Market Making Agent`, name the agent, add SOL, then select `Fund and deploy agent`. * For Liquidity Mode, continue to [Explore HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) or build a custom setup from [HawkFi automations](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). {% endstep %} {% step %} ### Fund the live setup deliberately Use an amount that matches the risk you are prepared to monitor. A strong historical result does not remove market, inventory, execution, or impermanent-loss risk. {% endstep %} {% step %} ### Monitor live behavior Compare the live Agent or LP position with the behavior you expected from Laboratory. Market conditions will not replay the backtest exactly. {% endstep %} {% endstepper %} ## How to know you are ready Before going live, you should be able to explain: 1. Why the setup fits the pool and market behavior you tested. 2. Which drawdown, inventory, or range tradeoffs appeared in the backtest. 3. What you will monitor after deployment. 4. Which result would make you pause, widen, reduce, or retest the setup. ## Go deeper * [Test a Market Making Setup](/whitepaper/hawkfi-laboratory/market-making) * [Test an LP Setup](/whitepaper/hawkfi-laboratory/liquidity-providing) * [Monitor and Manage Your Agent](/whitepaper/hawkfi-agents/monitor-and-manage-your-agent) * [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) # HawkFi Models Deploy battle-tested quant models in a single click. ## What are HawkFi Models? HawkFi Models are battle-tested strategies optimized for specific asset classes and market regimes A model defines the starting liquidity shape, included automations, and default trigger logic. Variants keep the same core strategy but change the range width, rebalance behavior, or directional setup. {% hint style="info" %} You can also [build your own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) {% endhint %} ## Strategy Scenarios
Use this page as the model picker. Start with the market environment, then open the model family that matches how you want the position to behave. | Market environment | Start with | Why | | --------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------- | | Early launch correction and retracement | [Heart Attack](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) | Built for early, high volume token launches where fast corrections can create LP entries. | | High volume near current price |

High Frequency Liquidity (HFL)


Precision Curve

| Both keep liquidity dense around the active bin for concentrated fee generation. | | High volatility and choppy market |

Precision Hybrid


Precision Flip

| Both combine fee generation with swing trading gains as price moves through the range. | | Slow Multi hour to multi day market |

Multiday Cook Up (MCU)

Precision Hybrid

| Both fit longer holding windows where the position still needs active range management. | ## Models | Strategy family | Overview | Variants | | ------------------------------ | ---------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Precision Flip | 2x more concentrated fee-generation and maximize swing trading gains with high-frequency liquidity shaping | [Precision Flip Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-flip/precision-flip-ultra-wide) | | Precision Curve | 2x more concentrated fee-generation with high-frequency liquidity reshaping |

Precision Curve + Rebalance

Precision Curve Wide

Precision Curve Ultra Wide

| | Precision Hybrid | Maximize swing trading gains while generating fees with high-frequency liquidity reshaping |

Precision Hybrid + Rebalance

Precision Hybrid Wide

Precision Hybrid Ultra Wide

| | High Frequency Liquidity (HFL) | Highly concentrated fee generation from tight-range, fast 0-minute swapless auto-rebalances |

HFL Tight

HFL Wide

| | Multiday Cook Up (MCU) | Best for multi-hour to multi-day LP in sideways & upward-trending price action | [MCU Curve](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu/multi-day-cook-up-mcu-curve) | | Heart Attack | Best for shallow price corrections in early & high volume-token launches |


Heart Attack Wide

Heart Attack Ping Pong (Bid-Ask-Flip)

| ## Related Pages * [HawkFi | Agent Terminal](/whitepaper) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) # Precision Flip 2x more concentrated fee-generation and maximize swing trading gains with high-frequency liquidity shaping ## What is Precision Flip
Precision Flip is a HawkFi Model designed to adaptively alternate between maximizing fee generation during volume spikes and maximizing swing trading gains during volatility spikes. ## Model Overview While this is a model with a combination of automations, the automations are still customizable to your liking. | Model | LP Details | | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Enhanced multi-hour to multi-day LP returns from both maximum fee concentration and buy-low, sell-high swing trading gains. | | How it works |

Precision Flip is a HawkFi model that starts in Precision Curve, then flips to Precision Hybrid when price reaches the position edges.

Curve mode keeps liquidity dense around the active bin (pool price) for maximum fee capture. Hybrid mode maintains a 50/50 Spot + Bid-ask distribution to keep printing fees while positioning for two-way swings.

Precision Flip continuously flips between these two liquidity shapes, with an optional flip buffer.

\*Free bin initialization fees, covered by HawkFi

| | Ideal entry | During sideways or volatile/choppy price action: wide, double-sided | ## Model Building Blocks
Model AutomationsEffectDefault settings
Auto-compound (AC)Maximize fee printing by automatically compounding position size from fees generated.On
Reshape Liquidity (RL)Keeps Curve liquidity concentrated around the active bin, then flips into a 50/50 Spot + Bid-ask liquidity distribution near the position edges.

Starting Shape: 5 bins, Curve

Alternative shape: 12 bins, Hybrid (50% Spot, 50% Bid-ask)



Flip buffer		Customizable buffer before Precision Flip switches between Precision Curve and Precision Hybrid when price reaches the position edges.2 bins
{% hint style="info" %} You can customize, change, or add more automations to your model based on market conditions and personal preferences. {% endhint %} ## Why use Precision Flip Precision Flip exists for LPs who want a model that can stay fee-concentrated near current price, then shift into a more swing-aware liquidity shape at the edges. It fits the middle ground between Precision Curve and Precision Hybrid. If the market stays useful near the center, Curve mode stays efficient. If price pushes outward, Hybrid mode is better suited for two-way swings without abandoning fee generation. If you want more range coverage from the same family, use the ultra-wide variant. For the full model map, go back to [Models](/whitepaper/models-and-automations-library/hawkfi-models) ## Variants of this Model * [Precision Flip Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-flip/precision-flip-ultra-wide) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: # Precision Flip Ultra Wide 2x more concentrated fee-generation and maximize swing trading gains with high-frequency liquidity shaping across an ultra-wide range ## What is Precision Flip Ultra Wide Precision Flip Ultra Wide is a HawkFi model variation of [Precision Flip](/whitepaper/models-and-automations-library/hawkfi-models/precision-flip). It uses the same Precision Flip behavior, but across an ultra wide range. ## Model Overview | Model | LP Details | | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Enhanced multi-hour to multi-day LP returns from both maximum fee concentration and buy-low, sell-high swing trading gains when the LP wants more range coverage than standard Precision Flip. | | How it works |

Precision Flip Ultra Wide is a HawkFi model variation that starts in Precision Curve, then flips to Precision Hybrid when price reaches the position edges.

It keeps the same Curve to Hybrid flip behavior as the parent model, but uses an ultra wide range to give the position more room before edge-driven behavior matters.

Free bin initialization fees, covered by HawkFi

| | Ideal entry | During sideways or volatile/choppy price action: ultra wide, double-sided | ## What changes from Precision Flip? | What stays the same | What changes in Ultra Wide | | ----------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | Same parent model: Precision Flip | Ultra wide range coverage | |

Same liquidity shape behavior:

Curve ⇄ 50% Spot 50% Bid-Ask

| More room before price reaches the position edges | | Same included automations: Auto-compound (AC), Reshape Liquidity (RL), and optional flip buffer | Better fit when the LP wants Precision Flip behavior without the standard model width | ## Model Building Blocks | Model Automation | Why it is included | Default Settings | | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------- | | Auto-compound (AC) | Maximize fee printing by automatically compounding position size from fees generated. | On | | Reshape Liquidity (RL) | Keeps Curve liquidity concentrated around the active bin, then flips into a 50/50 Spot + Bid-Ask liquidity distribution near the position edges. |

Starting Shape: 5 bins, Curve

Alternative shape: 12 bins, Hybrid (50% Spot, 50% Bid-ask)

| | Flip buffer | Adds a buffer before switching between Precision Curve and Precision Hybrid at the position edges. | 2 BINS | ## Why choose Precision Flip Ultra Wide? Precision Flip Ultra Wide is for people who want the same parent Precision Flip behavior, but with more range coverage. The simple tradeoff is: * Standard Precision Flip is the tighter parent version. * Precision Flip Ultra Wide gives more room across the range before edge-triggered flip behavior matters. * You choose Ultra Wide when you still want Precision Flip behavior, but do not want the standard model width. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Flip](/whitepaper/models-and-automations-library/hawkfi-models/precision-flip) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve) * [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Curve 2x more concentrated fee-generation with high-frequency liquidity reshaping ## What is Precision Curve
Precision Curve is a HawkFi model that generate more fees by keeping liquidity concentrated near the current pool price as the market moves. ## Model Overview | Model | LP Details | | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Maximize fee generation of multi-hour to multi-day LP with wide ranges to print from uptrend, sideways, or dip price actions. | | How it works |

Wide or 69 bin-range LP with real-time liquidity reshaping to keep Curve liquidity concentrated around active bin (pool price), without added IL risk from rebalancing the full price range by default.

Precision Curve is the fee-focused Curve model inside Models Library. The Wide, Ultra Wide, and Rebalance pages show how that same base model changes for different range needs.

Free bin initialization fees, covered by HawkFi

| | Ideal entry |
  • During price corrections: wide, single-side SOL only
  • During price uptrends: wide, single-side token only
  • During sideways price: wide, double-sided
| ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking. | Model Automations | LP effect | Default settings | | ---------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------- | | Auto-compound (AC) | Maximize fee printing by automatically compounding position size from fees generated. | On | | Reshape Liquidity (RL) | High-frequency liquidity reshaping whenever active bin moves by a set trigger so Curve liquidity stays concentrated around current price. | 5 bins | {% hint style="info" %} You can customize, change, or add more automations to your model based on market conditions and personal preferences. {% endhint %} ## Why use Precision Curve Precision Curve is the simple fee-focused model for LPs who want a setup that stays useful near current price instead of leaving liquidity static as price drifts. Use the base model when you want the standard Curve behavior. Move to a wider variant when you want more range coverage, or to the rebalance variant when you want the full range to follow price. For the full Models map, go back to [Models](/whitepaper/models-and-automations-library/hawkfi-models). ## Variants of this Model * [Precision Curve + Rebalance](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve/precision-curve-+-rebalance) * [Precision Curve Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve/precision-curve-wide) * [Precision Curve Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve/precision-curve-ultra-wide) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: # Precision Curve + Rebalance 2x more concentrated fee-generation with high-frequency liquidity reshaping and ## What is Precision Curve + Rebalance Precision Curve + Rebalance is a HawkFi model variation of [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). It uses the same Precision Curve behavior, but adds Ping Pong Auto-rebalance so the full range can follow price instead of staying fixed. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). For where this model sits in HawkFi docs, see [Model](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LPs that want Precision Curve fee concentration, but also want the full range to follow price through larger movement. | | How it works | Uses the parent Precision Curve setup, then adds Auto-rebalance with `UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68`. RL keeps Curve liquidity concentrated around active bin (pool price), while AR can move the full range when the rebalance condition is met. | | Ideal entry | Markets where the LP still wants Curve concentration near current swap flow, but expects price to keep moving far enough that a fixed range may become less useful. | ## What changes from Precision Curve? | What stays the same | What changes in Precision Curve + Rebalance | | ---------------------- | -------------------------------------------------------------------------------------------------------------------------- | | Curve liquidity shape | The position still uses `CURVE` to concentrate liquidity around active bin (pool price). | | Reshape Liquidity (RL) | RL still uses `5 BINS` as the visible model default for Curve reshaping. | | Auto-compound (AC) | `AC` remains included so earned fees or rewards can compound back into the position. | | Full range behavior | This variation adds `AR` with `UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68`, so the full range can move in either direction. | ## Model Building Blocks | Model components | Why it is included | Default Settings | | ---------------------- | ------------------------------------------------------------------------------------------------------ | ----------------------------------------- | | Liquidity shape | Keeps the parent model's concentrated Curve fee-generation profile. | CURVE | | Auto-compound (AC) | Keeps earned fees or rewards working back into the position. | ON | | Reshape Liquidity (RL) | Keeps Curve liquidity concentrated around active bin (pool price) while the position remains in range. | 5 BINS | | Auto-rebalance (AR) | Adds full range movement so the model can follow larger price moves. | UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68 | For deeper understanding of AC, RL, AR, and Ping Pong, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). ## Why choose Precision Curve + Rebalance? Precision Curve + Rebalance is for people who want the same Precision Curve fee concentration, but with full range movement added. The simple tradeoff is: * Precision Curve keeps the range fixed and focuses on reshaping inside that range. * Precision Curve + Rebalance adds Ping Pong AR so the full range can follow price. * Choose this variation when you still want Curve behavior, but do not want the model anchored to one original range while price keeps moving. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Curve Wide 2x more concentrated fee-generation with high-frequency liquidity reshaping and wide coverage ## What is Precision Curve Wide Precision Curve Wide is a HawkFi model variation of [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). It uses the same Precision Curve behavior, but changes the range width from the parent 69-bin setup to 149 bins. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview
ModelLP Details
Best forMulti-hour to multi-day LP that wants the same fee-focused Curve behavior as Precision Curve, but with 149-bin range coverage instead of the parent 69-bin setup.
How it worksPrecision Curve Wide keeps Curve liquidity concentrated around the active bin (pool price) with real-time liquidity reshaping, while expanding range coverage from 69 bins to 149 bins.

It keeps the same parent model behavior and included automations, but changes the range width so the position has more room before range management is needed.

*Free bin initialization fees, covered by HawkFi
Ideal entryDuring sideways, grinding, or correction price action when the LP still wants Precision Curve behavior, but does not want the tighter 69-bin parent model width.
## What changes from Precision Curve?
What stays the sameWhat changes in Wide
Same parent model: Precision CurveRange width changes from 69 bins to 149 bins
Same liquidity shape: CurveMore room before range management is needed
Same included automations: AC and RLBuilt for LPs who want the same fee-focused Curve behavior without the standard 69-bin model width
## Model Building Blocks
Model componentsWhy it is includedDefault Settings
Range widthDifferentiates Wide from the 69-bin parent model.149 BINS
Liquidity shapeKeeps liquidity concentrated around the active bin.CURVE
Auto-compound (AC)Keeps earned fees working inside the position.AC
Reshape Liquidity (RL)Keeps the Curve shape active as price moves inside the wider range.5 BINS
For deeper understanding of AC, RL, AR, and Ping Pong, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). ## Why choose Precision Curve Wide? Precision Curve Wide is for LPs who want the same parent Precision Curve behavior, but with 149-bin range coverage. The simple tradeoff is: * Precision Curve is the base parent version at 69 bins. * Precision Curve Wide gives more room across the range at 149 bins. * You choose Wide when you still want fee-focused Precision Curve behavior, but do not want the standard 69-bin model width. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve) * [Precision Curve Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve/precision-curve-ultra-wide) * [Build your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Curve Ultra Wide 2x more concentrated fee-generation with high-frequency liquidity reshaping and ultra wide coverage ## What is Precision Curve Ultra Wide Precision Curve Ultra Wide is a HawkFi model variation of [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). It uses the same Precision Curve behavior, but changes the range width from the parent 69-bin setup to 250 bins. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models) {% endhint %} ## Model Overview | Model | LP Details | | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LP that wants the same fee-focused Curve behavior as Precision Curve, but with 250-bin range coverage instead of the parent 69-bin setup. | | How it works |

Precision Curve Ultra Wide keeps Curve liquidity concentrated around the active bin (pool price) with real-time liquidity reshaping, while expanding range coverage from 69 bins to 250 bins.

It keeps the same parent model behavior and included automations, but changes the range width so the position has more room before range management is needed.

\*Free bin initialization fees, covered by HawkFi

| | Ideal entry | During sideways, grinding, or correction price action when the LP still wants Precision Curve behavior, but does not want the tighter 69-bin parent model width. | ## What changes from Precision Curve? | What stays the same | What changes in Ultra Wide | | ------------------------------------ | -------------------------------------------------------------------------------------------------- | | Same parent model: Precision Curve | Range width changes from 69 bins to 250 bins | | Same liquidity shape: Curve | More room before range management is needed | | Same included automations: AC and RL | Built for LPs who want the same fee-focused Curve behavior without the standard 69-bin model width | ## Model Building Blocks | Model components | Why it is included | Default Settings | | ---------------------- | --------------------------------------------------------------------- | ---------------- | | Range width | Differentiates Ultra Wide from the 69-bin parent model. | 250 BINS | | Liquidity shape | Keeps liquidity concentrated around the active bin. | CURVE | | Auto-compound (AC) | Keeps earned fees working inside the position. | AC | | Reshape Liquidity (RL) | Keeps the Curve shape active as price moves inside the 250-bin range. | 5 BINS | For deeper automation mechanics, see [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) or go back to [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve). ## Why choose Precision Curve Ultra Wide? Precision Curve Ultra Wide is for LPs who want the same parent Precision Curve behavior, but with 250-bin range coverage. The simple tradeoff is: * Precision Curve is the base parent version at 69 bins. * Precision Curve Ultra Wide gives more room across the range at 250 bins. * You choose Ultra Wide when you still want fee-focused Precision Curve behavior, but do not want the standard 69-bin model width. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Curve](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve) * [Precision Curve Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-curve/precision-curve-wide) * [Build Your Own Model](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Hybrid Maximize swing trading gains while generating fees with high-frequency liquidity reshaping ## What is Precision Hybrid?
Precision Hybrid is a HawkFi model built to generate fees while also capturing swing trading gains. * The default liquidity shape is a hybrid of 50% Spot and 50% Bid-Ask liquidity distribution around the active bin. It is the model family for LPs who want a more balanced fee plus swing-trading setup than a pure Curve or pure Bid-ask shape. | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Best for | Enhanced multi-hour to multi-day returns from both fee generation and dip or swing trading gains. | | How it works |

Precision Hybrid keeps a 50/50 hybrid between Spot liquidity and Bid-ask liquidity around the active bin. Spot helps keep liquidity dense near current price for stable fee capture. Bid-ask helps the position stay useful for two-way price movement and swing trading gains.

Free bin initialization fees, covered by HawkFi

| | Ideal entry | During price corrections: wide, single-side SOL only | | Simple why | Use Precision Hybrid when you want one model to do both jobs reasonably well: keep fee capture active near current price while staying positioned for swings. | ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking.
| Model Automations | What it does inside this model | | ---------------------- | ---------------------------------------------------------------------------------------- | | Reshape Liquidity (RL) | Keeps the Hybrid liquidity shape aligned around the active bin as price moves. | | Auto-compound (AC) | Can add earned fees back into the position to keep the model working with a larger base. | {% hint style="info" %} For exact automation mechanics, triggers, and configuration depth, use the [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). {% endhint %} ## Variants of Precision Hybrid Choose the variant based on how wide you want the working range to be, or whether you want the full range to follow price. * [Precision Hybrid + Rebalance](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-+-rebalance) * [Precision Hybrid Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-wide) * [Precision Hybrid Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-ultra-wide) # Precision Hybrid + Rebalance Maximize swing trading gains while generating fees with high-frequency liquidity reshaping and price following ## What is Precision Hybrid + Rebalance Precision Hybrid + Rebalance is a HawkFi model variation of [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). It uses the same Precision Hybrid behavior, but adds Ping Pong Auto-rebalance so the full range can follow price instead of relying only on Hybrid reshaping inside one working range. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LPs that want Precision Hybrid fee plus swing trading behavior, but also want the full range to keep following price through larger moves. | | How it works | Uses the parent Precision Hybrid setup, then adds Auto-rebalance with `UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68`. RL keeps the 50% Spot 50% Bid-Ask liquidity distribution aligned around active bin (pool price), while AR can move the full range when the rebalance condition is met. | | Ideal entry | Markets where the LP still wants Hybrid fee plus swing trading exposure, but expects price to move far enough that a fixed range may become less useful. | Precision Hybrid + Rebalance keeps 50% Spot 50% Bid-Ask liquidity active around active bin (pool price) while Ping Pong rebalance moves the full range. ## What changes from Precision Hybrid? | What stays the same | What changes in Precision Hybrid + Rebalance | | ---------------------- | -------------------------------------------------------------------------------------------------------------------------- | | Hybrid liquidity shape | The position still uses `50% SPOT 50% BID-ASK` to balance fee capture with swing trading exposure. | | Reshape Liquidity | RL still uses `34 BINS` as the visible model default for Hybrid reshaping. | | Auto-compound | `AC` remains included so earned fees or rewards can compound back into the position. | | Full range behavior | This variation adds `AR` with `UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68`, so the full range can move in either direction. | ## Strategy Building Blocks | Model components | Why it is included | Default Settings | | ---------------------- | -------------------------------------------------------------------------------------------------------------------- | ----------------------------------------- | | Liquidity shape | Keeps the parent model's balance between fee capture near current price and swing trading exposure across the range. | 50% SPOT 50% BID-ASK | | Auto-compound (AC) | Keeps earned fees or rewards working back into the position. | AC | | Reshape Liquidity (RL) | Keeps the Hybrid distribution aligned around active bin (pool price) while the position remains in range. | 34 BINS | | Auto-rebalance (AR) | Adds full range movement so the model can keep following larger price moves. | UP & DOWN, 0M COOLDOWN, PING PONG 68-0-68 | For deeper definitions of AC, RL, AR, and Ping Pong, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). ## Why choose Precision Hybrid + Rebalance? Precision Hybrid + Rebalance is for people who want the same Precision Hybrid balance between fee generation and swing trading gains, but with full range movement added. The simple tradeoff is: * Precision Hybrid keeps the range logic centered on Hybrid reshaping. * Precision Hybrid + Rebalance adds Ping Pong AR so the full range can follow price. * Choose this variation when you still want Hybrid behavior, but do not want the model anchored to one original range while price keeps moving. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid) * [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Hybrid Wide Maximize swing trading gains while generating fees with high-frequency liquidity reshaping and wide coverage ## What is Precision Hybrid Wide Precision Hybrid Wide is a HawkFi model variation of [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). It uses the same Precision Hybrid behavior, but changes the range width from the parent 69-bin setup to 149 bins. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LP that wants the same fee generation plus swing trading behavior as Precision Hybrid, but with 149-bin range coverage instead of the parent 69-bin setup. | | How it works |

Precision Hybrid Wide keeps the same 50/50 bid-ask + spot liquidity distribution around the active bin (pool price) with real-time liquidity reshaping, while expanding range coverage from 69 bins to 149 bins.

It keeps the same parent model behavior and included automations, but changes the range width so the position has more room before range management is needed.

Free bin initialization fees, covered by HawkFi

| | Ideal entry | During price corrections, volatile chop, or wider sideways ranges when the LP still wants Precision Hybrid behavior, but does not want the tighter 69-bin parent model width. | ## What changes from Precision Hybrid? | What stays the same | What changes in Wide | | ------------------------------------------ | --------------------------------------------------------------------------------------- | | Same parent model: Precision Hybrid | Range width changes from 69 bins to 149 bins | | Same liquidity shape: 50% Spot 50% Bid-Ask | More room before range management is needed | | Same included automations: AC and RL | Built for LPs who want the same Hybrid behavior without the standard 69-bin model width | ## Model Building Blocks | Model components | Why it is included | Default Settings | | ---------------------- | -------------------------------------------------------------------------------------------------------------------- | --------------------- | | Liquidity shape | Keeps the parent model's balance between fee capture near current price and swing trading exposure across the range. | 50% SPOT, 50% BID-ASK | | Auto-compound (AC) | Keeps earned fees or rewards working back into the position. | AC | | Reshape Liquidity (RL) | Keeps the Hybrid distribution aligned around active bin (pool price) while the position remains in range. | 74 BINS | For deeper automation mechanics, see [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) or go back to [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). ## Why choose Precision Hybrid Wide? Precision Hybrid Wide is for LPs who want the same parent Precision Hybrid behavior, but with 149-bin range coverage. The simple tradeoff is: * Precision Hybrid is the base parent version at 69 bins. * Precision Hybrid Wide gives more room across the range at 149 bins. * You choose Wide when you still want Precision Hybrid behavior, but do not want the standard 69-bin model width. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid) * [Precision Hybrid Ultra Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-ultra-wide) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Precision Hybrid Ultra Wide Maximize swing trading gains while generating fees with high-frequency liquidity reshaping and ultra wide coverage ## What is Precision Hybrid Ultra Wide? Precision Hybrid Ultra Wide is a variant of the parent [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid) model. It keeps the same 50% Spot 50% Bid-Ask liquidity shape and the same core included automations, but changes the model width from 69 bins to 250 bins. This variant exists for LPs who want the same Hybrid behavior with more range coverage before range management is needed. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LP that wants the same fee generation plus swing trading behavior as Precision Hybrid, but with 250-bin range coverage instead of the parent 69-bin setup. | | How it works |

Precision Hybrid Ultra Wide keeps the same 50/50 bid-ask + spot liquidity distribution around the active bin (pool price) with real-time liquidity reshaping, while expanding range coverage from 69 bins to 250 bins.

It keeps the same parent model behavior and included automations, but changes the range width so the position has more room before range management is needed.

Free bin initialization fees, covered by HawkFi

| | Ideal entry | During price corrections, volatile chop, or wider sideways ranges when the LP still wants Precision Hybrid behavior, but does not want the tighter 69-bin parent model width. | ## What Changes From Precision Hybrid | What stays the same | What changes in Ultra Wide | | ------------------------------------------ | --------------------------------------------------------------------------------------- | | Same parent model: Precision Hybrid | Range width changes from 69 bins to 250 bins | | Same liquidity shape: 50% Spot 50% Bid-Ask | More room before range management is needed | | Same included automations: AC and RL | Built for LPs who want the same Hybrid behavior without the standard 69-bin model width | ## Included Automations | Model components | Why it is included | Default Settings | | ---------------------- | -------------------------------------------------------------------------------------------------------------------- | -------------------- | | Liquidity shape | Keeps the parent model's balance between fee capture near current price and swing trading exposure across the range. | 50% SPOT 50% BID-ASK | | Auto-compound (AC) | Keeps earned fees or rewards working back into the position. | AC | | Reshape Liquidity (RL) | Keeps the Hybrid distribution aligned around active bin (pool price) while the position remains in range. | 124 BINS | For deeper automation mechanics, see [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) or go back to [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid). ## Why choose Precision Hybrid Ultra Wide? Precision Hybrid Ultra Wide is for LPs who want the same parent Precision Hybrid behavior, but with 250-bin range coverage. The simple tradeoff is: * Precision Hybrid is the base parent version at 69 bins. * Precision Hybrid Wide gives more room across the range at 149 bins. * Precision Hybrid Ultra Wide gives the maximum standard range coverage at 250 bins. * You choose Ultra Wide when you still want Precision Hybrid behavior, but want more room than both the standard and Wide model widths. ## Related pages * [Precision Hybrid](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid) * [Precision Hybrid Wide](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-wide) * [Precision Hybrid + Rebalance](/whitepaper/models-and-automations-library/hawkfi-models/precision-hybrid/precision-hybrid-+-rebalance) * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models) # High Frequency Liquidity (HFL) Highly concentrated fee generation from tight-range, fast 0-minute swapless auto-rebalances ## What is High Frequency Liquidity (HFL) Regular? High Frequency Liquidity (HFL) Regular is a HawkFi model for people who want highly concentrated fee generation from tight-range, fast 0-minute swapless auto-rebalances. ## Model Overview | Model | LP Details | | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | High-volume pools where concentrated fee generation matters and the LP wants the standard HFL setup before choosing a tighter or wider range variant. | | How it works |

HFL Regular uses SPOT liquidity with AA:SOL, AR UP & DOWN, 0M COOLDOWN, PING PONG 12-0-12, and SL:SOL @ -20% POOL PRICE.

The model keeps a tight Spot range active with fast swapless Ping Pong rebalances as price moves. The 12-0-12 Ping Pong range is the base HFL configuration. HFL Tight and HFL Wide change that range for more aggressive concentration or more coverage.

Free bin initialization fees, covered by HawkFi

| | Ideal entry |
  • During active sideways price action where fast fee-focused range-following can stay useful
  • When you want the standard HFL configuration
  • When you want concentrated fee generation without choosing the tighter or wider HFL variants first
| ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking. | | LP effect | Default settings | | ------------------------- | ------------------------------------------------------------------------------------ | ----------------------------------------- | | Liquidity shape | Keeps HFL focused on concentrated fee generation around the selected range. | SPOT | | Auto-accumulate Fees (AA) | Accumulates earned fees to SOL instead of compounding them into the active position. | AA:SOL | | Auto-rebalance (AR) | Moves the full LP range upward or downward as the HFL range is exited. | UP & DOWN, 0M COOLDOWN, PING PONG 12-0-12 | | Stop Loss (SL) | Adds the model downside exit condition. | SL:SOL @ -20% POOL PRICE | {% hint style="info" %} For deeper definitions of AA, AR, Ping Pong, and SL, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). {% endhint %} ## Why use HFL Regular? HFL Regular is the base HFL configuration. It is the first HFL model to use when you want the standard tight-range, fee-focused setup before deciding whether the pool needs a tighter or wider Ping Pong range. The simple range ladder is: * HFL Regular uses `12-0-12` as the base setup. * HFL Tight changes the range to `6-0-6` for more aggressive concentration. * HFL Wide changes the range to `18-0-18` for more coverage. ## Variants of this Model * [HFL Tight](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl/high-frequency-liquidity-hfl-tight) * [HFL Wide](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl/high-frequency-liquidity-hfl-wide) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # High Frequency Liquidity (HFL) Tight Aggressive HFL with boosted fee-generation from tighter ranges and 0-min swapless auto-rebalances ## What is HFL Tight High Frequency Liquidity (HFL) Tight is a HawkFi model variation of [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). It uses the same HFL behavior, but changes the Ping Pong range to `6-0-6` for tighter fee concentration and faster range-following. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | High-volume pools where the LP wants the most aggressive HFL range concentration instead of the base HFL Regular setup or the wider HFL Wide setup. | | How it works |

HFL Tight keeps the parent HFL setup of SPOT liquidity, AA:SOL, AR UP & DOWN, 0-minute swapless Ping Pong Auto-rebalance, and SL:SOL @ -20% POOL PRICE.

The variation changes the Ping Pong range to 6-0-6, making it the tightest HFL model range for more aggressive fee concentration near the active bin (pool price).

Free bin initialization fees, covered by HawkFi

| | Ideal entry |

- During active sideways price action where tight fee concentration can stay useful
- When the LP wants HFL behavior with the tightest model Ping Pong range
- When more aggressive range-following matters more than broader range coverage

| ## What changes from High Frequency Liquidity (HFL)? | What stays the same | What changes in Tight | | ------------------------------------------------- | ---------------------------------------------------------- | | Same parent model: High Frequency Liquidity (HFL) | Starting range width changes to `8 BINS` | | Same liquidity shape: SPOT | Ping Pong range changes to `6-0-6` | | Same included automations: AA, AR, and SL | Built for LPs who want the most aggressive HFL model range | ## Strategy Building Blocks While this is a model variation with a combination of automations, the automations are still customizable to your liking. | Model Components | LP effect | Default settings | | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- | | Liquidity shape | Keeps HFL focused on concentrated fee generation around the selected range. | SPOT | | Auto-accumulate Fees (AA) | Accumulates earned fees to SOL instead of compounding them into the active position. | AA:SOL | | Auto-rebalance (AR) | Moves the full LP range upward or downward as the HFL range is exited. | UP & DOWN, 0M COOLDOWN, PING PONG 6-0-6 | | Stop Loss (SL) | Adds the model downside exit condition. | SL:SOL @ -20% POOL PRICE | | (More Customizations Available) | After deploying a model, you can further customize your position automations based on market conditions and personal preferences. | Customizable | For deeper definitions of AA, AR, Ping Pong, and SL, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). For the full HFL model logic, go back to [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). ## Why choose HFL Tight? HFL Tight is for LPs who want the same parent HFL behavior, but with the tightest model Ping Pong range. The simple tradeoff is: * HFL Regular uses `12-0-12` as the base setup. * HFL Tight changes the range to `6-0-6` for more aggressive fee concentration. * You choose Tight when you still want HFL behavior, but want less range width than the standard HFL Regular setup. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl) * [HFL Wide](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl/high-frequency-liquidity-hfl-wide) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * Coming soon ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * Coming soon # High Frequency Liquidity (HFL) Wide Balanced HFL with steady fee-generation from tighter ranges and 0-min swapless auto-rebalances ## What is HFL Wide High Frequency Liquidity (HFL) Wide is a HawkFi model variation of [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). It uses the same HFL behavior, but changes the starting range width to `20 bins` and uses `Ping Pong Balance 18-18` for more range coverage and less aggressive range-following. {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | High-volume pools where the LP wants the same HFL behavior as the parent model, but with more range coverage than HFL Regular or HFL Tight. | | How it works |

HFL Wide keeps the parent HFL setup of SPOT liquidity, AA:SOL, AR UP & DOWN, 0-minute swapless Ping Pong Auto-rebalance, and SL:SOL @ -20% POOL PRICE.

The variation changes the starting range width to 20 BINS and uses PING PONG BALANCE 18-0-18, giving the position more room before the full LP range is moved upward or downward.

Free bin initialization fees, covered by HawkFi

| | Ideal entry |

- During active sideways price action where wider HFL coverage can stay useful
- When the LP wants the same HFL setup with less aggressive range-following than HFL Tight or HFL Regular
- When broader range coverage matters more than the tightest model fee concentration

| ## Image ## What changes from High Frequency Liquidity (HFL)? | What stays the same | What changes in Wide | | ------------------------------------------------- | ------------------------------------------------------------------------------ | | Same parent model: High Frequency Liquidity (HFL) | Starting range width changes to `20 BINS` | | Same liquidity shape: SPOT | Ping Pong Balance uses `18-0-18` | | Same included automations: AA, AR, and SL | Broader range coverage than HFL Regular at `14 BINS` and HFL Tight at `8 BINS` | ## Model Building Blocks While this is a model variation with a combination of automations, the automations are still customizable to your liking. | Model Components | LP effect | Default settings | | ------------------------- | ------------------------------------------------------------------------------------ | ----------------------------------------------------------------------- | | Liquidity shape | Keeps HFL focused on concentrated fee generation around the selected range. | SPOT | | Auto-accumulate Fees (AA) | Accumulates earned fees to SOL instead of compounding them into the active position. | AA:SOL | | Auto-rebalance (AR) | Moves the full LP range upward or downward as the HFL range is exited. | UP & DOWN, 0M COOLDOWN, STARTING RANGE 20 BINS, PING PONG BALANCE 18-18 | | Stop Loss (SL) | Adds the model downside exit condition. | SL:SOL @ -20% POOL PRICE | For deeper definitions of AA, AR, Ping Pong, and SL, use [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). For the full HFL model logic, go back to [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl). ## Why choose HFL Wide? HFL Wide is for LPs who want the same parent HFL behavior, but with the widest model starting range. The simple tradeoff is: * HFL Tight starts at `8 bins`. * HFL Regular starts at `14 bins` as the base setup. * HFL Wide starts at `20 bins`. * HFL Wide also uses `Ping Pong Balance 18-18`, which is wider than the tighter HFL variants. * You choose Wide when you still want HFL behavior, but want more range width than the standard HFL Regular setup. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [High Frequency Liquidity (HFL)](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl) * [HFL Tight](/whitepaper/models-and-automations-library/hawkfi-models/high-frequency-liquidity-hfl/high-frequency-liquidity-hfl-tight) * [Build Your Own Models](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Multi-day Cook Up (MCU) Best for multi-hour to multi-day LP in sideways & upward-trending price action ## What is Multiday Cook Up (MCU) Spot Multiday Cook Up (MCU) Spot is a HawkFi model for LPs who want Spot liquidity, Auto-compound, and up-only Auto-rebalance for sideways or upward-trending price action. ## Model Overview | Model | LP Details | | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Multi-hour to multi-day LP when the LP wants Spot liquidity with directional, up-only range management. | | How it works |

MCU Spot starts with Spot liquidity across the selected range. Auto-compound keeps earned fees working inside the position, while Auto-rebalance can move the full range upward when the up-only condition is met.

The model is built to keep participating when price moves higher, while avoiding automatic downward rebalances during temporary dips.

| | Ideal entry |

- Sideways price with upward bias: double-sided MCU Spot
- Steady uptrend: double-sided or token-heavier MCU Spot
- Temporary dips inside a broader uptrend: MCU Spot when the LP does not want automatic downside range resets

| ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking. | Model Automations | LP effect | Default settings | | ------------------- | ------------------------------------------------------------------------ | ----------------------------------------------- | | Liquidity shape | Uses Spot liquidity across the selected range. | SPOT | | Auto-compound (AC) | Compounds earned fees back into the active position. | AC | | Auto-rebalance (AR) | Moves the full range upward when the up-only rebalance condition is met. | UP ONLY, 10M COOLDOWN, +-15%\*, IN-RANGE BUFFER | {% hint style="info" %} For deeper automation mechanics, see the [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models), [Auto-compound](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-compound-ac), and [Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar). {% endhint %} ## Why use Multiday Cook Up (MCU) Spot Use MCU Spot when you want a slower, longer-horizon LP model that can follow upward price movement without automatically chasing every downside move. The simple idea is: * Spot liquidity gives broad participation across the selected range. * AC keeps generated fees active inside the position. * Up-only AR lets the range move higher when price trends up. For the full model map, go back to [Models](/whitepaper/models-and-automations-library/hawkfi-models). ## Variants of this Model * [MCU Curve](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu/multi-day-cook-up-mcu-curve) uses the same MCU behavior with Curve liquidity shape for more concentrated fee generation around the active bin. * [Multiday Cook Up (MCU)](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu) is the broader MCU overview page for comparing Spot and Curve versions. ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Multi-day Cook Up (MCU) Curve Best for multi-hour to multi-day LP in sideways & upward-trending price action that's more aggressive ## What is MCU Curve MCU Curve is a HawkFi model variation of [Multiday Cook Up (MCU)](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu). It uses the same MCU behavior, but changes the liquidity shape from Spot to Curve for denser fee concentration around active bin (pool price). {% hint style="info" %} Use this page for what changes in this variation. For the full model logic, see [Multiday Cook Up (MCU)](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Best for | Multi-hour to multi-day LP that wants the same up-only MCU range behavior, but with more concentrated liquidity around active bin (pool price) than MCU Spot. | | How it works |

MCU Curve keeps the parent MCU setup of AC plus AR Up Only with 10m cooldown and in-range buffer, but changes the liquidity shape to Curve.

That means the range behavior stays the same as MCU, while liquidity inside the range becomes more concentrated around active bin (pool price).

Free bin initialization fees, covered by HawkFi

| | Ideal entry | Sideways to upward-trending price action when the LP wants MCU's slower, up-only range management, but wants denser fee concentration than the Spot variation. | *MCU Curve keeps the same up-only MCU range behavior, but uses Curve liquidity for denser fee concentration around active bin.* ## What changes from Multiday Cook Up (MCU)? | What stays the same | What changes in MCU Curve | | ----------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | | Same parent model: Multiday Cook Up (MCU) | Liquidity shape changes from Spot to Curve | | Same included automations: AC and AR Up Only | Liquidity becomes more concentrated around active bin (pool price) | | Same range behavior: 10m cooldown, +-15%\*, in-range buffer | Built for LPs who want the same MCU range logic with denser fee concentration inside the range | ## Model Building Blocks | Model components | Why it is included | Default Settings | | ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------- | | Liquidity shape | Changes the parent Spot distribution into a more concentrated liquidity profile around active bin (pool price). | CURVE | | Auto-compound (AC) | Keeps earned fees or rewards working back into the position. | AC | | Auto-rebalance (AR) | Keeps the same parent MCU behavior of moving the range upward when the rebalance condition is met, without automatically following downside moves. | UP ONLY, 10M COOLDOWN, +-15%\*, IN-RANGE BUFFER | For deeper automation mechanics, see [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) or go back to [Multiday Cook Up (MCU)](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu). ## Why choose MCU Curve? MCU Curve is for LPs who want the same parent MCU range behavior, but with Curve liquidity concentration instead of the Spot variation. The simple tradeoff is: * MCU Spot keeps the same MCU range behavior with Spot liquidity. * MCU Curve keeps the same MCU range behavior with more concentrated Curve liquidity around active bin. * You choose MCU Curve when you still want MCU's up-only, multi-day LP behavior, but want denser fee concentration inside the range. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Multiday Cook Up (MCU)](/whitepaper/models-and-automations-library/hawkfi-models/multi-day-cook-up-mcu) * [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Heart Attack Best for shallow price corrections in early & high volume-token launches ## What is Heart Attack Tight Heart Attack Tight is a HawkFi model for shallow price corrections in early and high-volume token launches. ## Model Overview | Model | LP Details | | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Shallow price corrections in early and high-volume token launches where fast LP entry and a tight Spot range matter more than wide downside coverage. | | How it works |

Heart Attack Tight is a HawkFi model that uses a tight-range Spot position to keep liquidity near the active price for quick fee generation during shallow corrections.

Take Profit (TP) can close the position at the configured profit target and output to SOL.

| | Ideal entry | During shallow price corrections: tight, single-side SOL only | ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking. | Model Automation | LP effect | Default settings | | ------------------------------- | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------- | | Spot liquidity shape | Tight-range Spot liquidity keeps capital concentrated near current price for quick fee generation during shallow corrections. | Spot | | Take Profit (TP) | Closes the position when the configured Take Profit condition is reached and outputs to SOL. | TP:SOL, 7% profit, customizable | | (More Customizations Available) | After deploying a Model, you can further customize your position automations based on market conditions and personal preferences. | Customizable | {% hint style="info" %} For deeper automation mechanics, see the [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). {% endhint %} ## Why use Heart Attack Tight Heart Attack Tight is for launch conditions where price pulls back, volume is still active, and the LP wants a tight Spot position instead of a wider defensive setup. The simple reason to use it: keep the setup focused on shallow correction fee generation, then let TP:SOL handle the exit when the configured profit condition is reached. ## Variants of this Model * [Heart Attack Wide](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack/heart-attack-wide) * [Heart Attack Ping Pong (Bid-Ask-Flip)](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack/heart-attack-ping-pong-bid-ask-flip) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Heart Attack Wide Best for deep price corrections in early & high volume-token launches ## What is Heart Attack Wide Heart Attack Wide is a variant of the HawkFi [Heart Attack](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) model for deeper price corrections in early and high-volume token launches. It gives wider downside coverage for deeper launch corrections with Bid-Ask liquidity and auto-TP to SOL ## Model Overview | Model | LP Details | | ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Deeper price corrections in early and high-volume token launches where wider downside coverage matters more than tight fee concentration. | | How it works |

Compared with the parent Heart Attack model, Heart Attack Wide shifts the setup into a wider Bid-Ask position so the LP can stay useful through deeper pullbacks and retracement setups.

Take Profit (TP) can close the position at the configured profit target and output to SOL.

| | Ideal entry | During deeper price corrections: wide, single-side SOL only | ## Model Building Blocks While this is a model with a combination of automations, the automations are still customizable to your liking. | Model Automation | LP effect | Default settings | | ----------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------- | | Bid-Ask liquidity shape | Compared with Heart Attack Tight, this variant uses a wider Bid-Ask distribution to place deeper downside bids while keeping asks ready for retracement exits. | Bid-Ask | | Take Profit (TP) | Closes the position when the configured Take Profit condition is reached and outputs to SOL. | TP:SOL, 7% profit, customizable | For deeper automation mechanics, see the [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). ## Why use Heart Attack Wide Heart Attack Wide is for launch conditions where the correction looks deeper than a tight Spot setup can comfortably cover, but the LP still wants a simple model with SOL-denominated exits. The simple reason to use it: widen the downside coverage versus Heart Attack Tight, keep the model focused on deeper correction entries, then let TP:SOL handle the exit when the configured profit condition is reached. ## Variants of this Model * [Heart Attack Tight](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) * [Heart Attack Ping Pong (Bid-Ask-Flip)](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack/heart-attack-ping-pong-bid-ask-flip) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Heart Attack Ping Pong (Bid-Ask-Flip) Best for deep price corrections and retracment in early & high volume-token launches ## What is Heart Attack Ping Pong (Bid-Ask-Flip) Heart Attack Ping Pong (Bid-Ask-Flip) is a HawkFi model variation of the HawkFi [Heart Attack](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) model. It uses the same Heart Attack correction and retracement logic, but adds automations to flip liquidity once conditions are met. {% hint style="info" %} Use this page for what changes in this variation. For the full parent model logic, see [Heart Attack](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack). For where this model sits in HawkFi docs, see [Models](/whitepaper/models-and-automations-library/hawkfi-models). {% endhint %} ## Model Overview | Model | LP Details | | ------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Deep correction and retracement setups in early and high-volume token launches, where the position may need to move lower before the bounce setup plays out. | | How it works |

Compared with the parent Heart Attack model, this variation uses Bid-Ask liquidity plus down-only Ping Pong AR with a 69-0-69 range setup.

The variant keeps the Heart Attack focus on launch correction entries, but adds range movement lower, TP:SOL for profit exits, and SL:SOL for pool price dip protection.

| | Ideal entry | During deep launch corrections with expected retracement: wide, single-side SOL only | ## What changes from Heart Attack? | What stays the same | What changes in Heart Attack Ping Pong | | ---------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- | | Still belongs to the Heart Attack model family for early, high-volume token launch corrections and retracements. | Adds down-only Ping Pong AR so the working range can reset lower when the correction continues. | | Still uses SOL-denominated exits as the clean model outcome. | Adds both TP:SOL and SL:SOL, so the variant has a profit-taking exit and a pool price dip protection exit. | | Still targets correction entries where single-side SOL can be deployed into a launch pullback. | Uses Bid-Ask liquidity with a 69-0-69 Ping Pong setup, making it more directional and more defensive than the simpler Heart Attack variants. | ## Model Building Blocks While this is a model variation with a combination of automations, the automations are still customizable to your liking. | Model components | Why it is included | Default Settings | | ----------------------- | -------------------------------------------------------------------------------------------------- | ----------------------------------------------- | | Bid-Ask liquidity shape | Places directional liquidity for deeper correction and retracement setups. | Bid-Ask | | Auto-rebalance (AR) | Lets the variant keep following downside continuation instead of staying fixed at the first range. | Down Only, 0 minute cooldown, Ping Pong 69-0-69 | | Take Profit (TP) | Closes the position into SOL when the configured profit condition is reached. | TP:SOL, 7% profit, customizable | | Stop Loss (SL) | Closes the position into SOL if the configured pool price dip condition is reached. | SL:SOL for pool price dip protection | For deeper automation mechanics, see the [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models). ## Why choose Heart Attack Ping Pong (Bid-Ask-Flip)? Heart Attack Ping Pong is for launch conditions where the correction may be too deep or too fast for the simpler Heart Attack versions. The simple tradeoff is: * Heart Attack Tight keeps the setup simpler and tighter for shallow corrections. * Heart Attack Wide adds wider Bid-Ask coverage for deeper corrections. * Heart Attack Ping Pong adds down-only Ping Pong AR plus SL:SOL when the setup needs the range to keep moving lower and still preserve SOL-denominated exits. ## Related pages * [Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Heart Attack](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) * [Heart Attack Tight](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack) * [Heart Attack Wide](/whitepaper/models-and-automations-library/hawkfi-models/heart-attack/heart-attack-wide) * [Automation Library](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models) * [Ping Pong Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/ping-pong-auto-rebalance) * [Take Profit](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/take-profit-tp) * [Stop Loss](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/stop-loss-sl) ## Tutorial Videos & Case Studies * (Coming soon) ## More Questions? * Join our Discord for questions & discussions on HFL: ## More Infographics * (Coming soon) # Build Your Own Models HawkFi Models are built from automations HawkFi Automations are the building blocks that power HawkFi Models. Each automation controls one part of how your position behaves: how liquidity is shaped, when the range moves, how fees are handled, and when the position exits. Use this section as the automation map before going deeper into each feature. ## Automation Building Blocks * [Reshape Liquidity (RL)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/reshape-liquidity-rl) is a HawkFi automation that dynamically reshapes your liquidity distribution to stay concentrated around the active bin as price moves within your range. * [Auto-rebalance (AR)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar) is a HawkFi automation that strategically adjusts the distribution of assets between different tokens in a pool to maintain an optimal position within the market's price range. * [Swapped Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/swapped-auto-rebalance) is the HawkFi Auto-rebalance (AR) type that moves the position range while swapping assets to match the required deposit ratio for another range. * [Swapless Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/swapless-auto-rebalance) is the HawkFi Auto-rebalance (AR) type that moves the position range while keeping original assets intact for another range. * [Ping Pong Auto-rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/ping-pong-auto-rebalance) is an Advanced swapless Auto-rebalance (AR) mode that alternates rebalance behavior between AR down and AR up range setups. * [Auto-compound (AC)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-compound-ac) is a HawkFi automation that automatically reinvests trading volume fees or rewards back into your position. * [Auto-accumulate Fees (AA)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-accumulate-fees-aa) is a HawkFi automation that strategically lets you accumulate fees into your HawkFi wallet. * [Take Profit (TP)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/take-profit-tp) is a HawkFi automation that automatically closes your position once a specific profit target is reached. * [Stop Loss (SL)](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/stop-loss-sl) is a HawkFi automation that automatically closes your position once a selected downside condition is reached. # Reshape Liquidity (RL) Concentrate liquidity to maximize fee-generation or swing trading gains ## **What is Reshape Liquidity (RL)?**
Reshape Liquidity (RL) is a HawkFi automation that dynamically reshapes your liquidity distribution to stay concentrated around the active bin as price moves within your range. ## **How does Basic Reshape Liquidity (RL) work?** Reshape Liquidity (RL) auto reshapes liquidity when the active bin, or pool price, moves beyond the configured trigger bins. Example: when the pool price moves beyond 5 bins, your position's liquidity distribution will be auto reshaped to Curve. ## **Reshape Liquidity Basic Customizations:** | Customize | What it controls | | ------------------------------- | ------------------------------------------------------------------------------------------------------------------------ | | Liquidity Shape After Rebalance |

The shape HawkFi reshapes the position into after Basic RL triggers.

Example: Curve.

| | Allowed Bin Movement |

The number of bins the active bin can move before Basic RL triggers.

Current possible range: 1 to 51 bins.

| {% hint style="info" %} Note: Allowed Bin Movement determines how frequently RL reshapes your liquidity. A lower number reshapes more aggressively for tighter concentration. A higher number reshapes less frequently and can fit wider ranges or lower maintenance positions. {% endhint %} ## **Reshape Liquidity Advanced Customizations:** Advanced RL adds shape flipping near the edge of the position.
CustomizeExampleWhat it controls
Starting ShapeCurveThe starting shape used by the position.
Allowed Bin Movement5 binsHow far price can move before reshaping back to the Starting Shape.
Flip Buffer5 binsHow close price can get to the edge before flipping to the Alternate Shape.
Alternate ShapeHybrid: 50% Spot, 50% Bid-AskThe after shape used by the position.
Alternate Shape Allowed Bin MovementHybrid: 50% Spot, 50% Bid-AskThe shape used after the edge flip.
Alternate Allowed Bin Movement12 binsHow far price can move before reshaping back to the Alternate Shape.
Alternate Flip Buffer2 binsHow close price can get to the edge before flipping back to the Starting Shape.
### How Reshape Liquidity (RL) behaves per strategy
StrategyHow RL BehavesWhat is it trying to do?
Precision CurveReshapes liquidity back into a Curve around the active bin.Keep liquidity near current price for fee concentration.
Precision HybridReshapes liquidity back into the selected Bid Ask shape.Adapt the Hybrid shape as price moves through volatility.
Precision FlipAdvanced RL can flip between Starting Shape and Alternative Shape near position edges.Keep the starting liquidity shape and alternative liquidity shape.
### FAQs for Reshape Liquidity (RL)
How is it different from Auto-rebalance (AR)? Unlike the HawkFi Auto-rebalance (AR) automation, Reshape Liquidity (RL) keeps your range fixed and reshapes the liquidity within it. This helps maximize fee capture without triggering unnecessary rebalances that can increase IL exposure.
AutomationWhat changes
Reshape LiquidityThe liquidity distribution inside the range.
Auto-rebalanceThe full position range.
# Auto-rebalance (AR) Strategically auto-adjusts the distribution of assets ## What is Auto-rebalance (AR)? Auto-rebalance (AR) is a HawkFi automation that strategically adjusts the distribution of assets between different tokens in a pool to maintain an optimal position within the market’s price range.
## How does Basic Auto-rebalance (AR) work? Auto-rebalance (AR) closes or adjusts the old range and opens a new range based on the selected rebalance type and mode. ## Auto-rebalance (AR) types | Type | What it does | Go deeper | | ------------------ | ---------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | | Swapped Rebalance | Moves the position range and uses swaps during the rebalance process. | [Swapped Rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/swapped-auto-rebalance) | | Swapless Rebalance | Moves the position range without performing a swap. | [Swapless Rebalance](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/swapless-auto-rebalance) | | Ping Pong | Advanced AR behavior that alternates rebalance behavior between two configured directions or ranges. | [Ping Pong](/whitepaper/models-and-automations-library/hawkfi-models/build-your-own-models/auto-rebalance-ar/ping-pong-auto-rebalance) | ## Auto-rebalance (AR) Shared Customizations These settings can apply across AR setups depending on the selected type and mode.
UI fieldExampleWhat it controls
Deposit ModeAuto-swap or No swapControls whether HawkFi swaps assets to match the required deposit ratio or keeps withdrawn assets intact for deposit.
Auto-Rebalance Deposit Slippage3% slippageSets the slippage limit used when AR deposits into the new position.
Auto-Rebalance Swap SlippageDynamic, max 5% slippageSets the swap slippage limit when Auto-swap is used.
AR Cooldown1 hourControls how soon AR can trigger again after a directional rebalance. Current UI supports 0 minutes to 24 hours.
Rebalance BufferNone, Price, or TimeAdds an optional buffer condition before AR executes.
## How Auto-rebalance (AR) behaves per strategy | Strategy | What AR is used | How AR behaves | Goal | | ---------------------------- | ------------------------ | ------------------------------------------------------------------- | ---------------------------------------------------------- | | Precision Hybrid + Rebalance | Ping Pong Auto-rebalance | AR can move the full range while Hybrid manages shape exposure. | Keep the Hybrid position active as market conditions move. | | Precision Curve + Rebalance | Ping Pong Auto-rebalance | AR can move the full range when the selected rebalance rule is met. | Keep the Curve position working near the active bin. | | HFL | Ping Pong Auto-rebalance | AR can move the range frequently as price moves. | Keep a tight range active near current price. | | MCU | Swapped Auto-rebalance | AR can move the range based on directional or timing rules. | Support longer timeframe directional LP management. | ## FAQs for Auto-rebalance (AR)
How is Auto-rebalance different from Reshape Liquidity (RL)? Auto-rebalance moves the full position range. Reshape Liquidity keeps the range fixed and reshapes liquidity inside that range. Use AR when the position range itself needs to move. Use RL when the range should stay fixed but the liquidity shape needs to stay useful around the active bin.
How should I choose between Swapped and Swapless Rebalance? Use Swapped Rebalance when you want to do traditional rebalance with swaps. Use Swapless Rebalance when you want to save on swap fees.
Does Auto-rebalance guarantee better returns? Auto-rebalance helps keep the position range closer to the active bin when the configured condition is met. It optimizes positions earn more fees, but results still depend on market conditions, volume, price movement, and strategy setup.
# Swapped Auto-rebalance Move your position in range to earn fees with swap-based rebalance ## What is Swapped Rebalance? Swapped Rebalance is the HawkFi Auto-rebalance (AR) type that moves the position range while swapping assets to match the assets for another range.
## How does Swapped Rebalance work? Swapped Rebalance closes or adjusts the old range and opens a new range based on the selected mode. Example: if price moves beyond the configured AR trigger, HawkFi can move the range and use the selected liquidity shape on rebalance. ## Swapped Rebalance Modes | Mode | Example | What it controls | | -------------- | -------------------------------------------- | ----------------------------------------------------------------- | | Fixed Schedule | Rebalance every 1 hour | Rebalances based on time instead of price direction. | | Up or Down | Rebalance up or down after 5 minute cooldown | Lets the range follow price in both upward and downward movement. | | Up only | Rebalance up after 5 minute cooldown | Lets the range follow upward price movement only. | | Down only | Rebalance up after 5 minute cooldown | Lets the range follow downward price movement only. | {% hint style="info" %} Note: AR Cooldown is the time HawkFi must wait between auto-rebalances. You can set this as low as 0 minute for close-to-realtime execution or as high as 24 hours. {% endhint %} ## Swapped Rebalance Technical Customizations | UI field | Example | What it controls | | ------------------------------- | ---------------------------- | ---------------------------------------------------------------------------------------- | | AR Cooldown | 0 minute | Controls how soon Up or Down, Up only, or Down only can trigger again after a rebalance. | | Auto-Rebalance Deposit Slippage | 3% slippage | Sets the slippage limit used when AR deposits into the new position. | | Liquidity Shape on Rebalance | Spot, Curve, Bid-Ask, Hybrid | Sets the liquidity shape used after the rebalance. | ## FAQs for Swapped Rebalance
How is Swapped Rebalance different from Swapless Rebalance? Swapped Rebalance may use swaps during the rebalance process. Swapless Rebalance moves the position range without performing a swap.
When does AR Cooldown apply? AR Cooldown applies to Up or Down, Up only, and Down only modes.
# Swapless Auto-rebalance Move your position in range to earn fees with swap-based rebalance ## What is Swapless Rebalance? Swapless Rebalance is the HawkFi Auto-rebalance (AR) type that moves the position range while keeping original assets intact for another range.
## How does Swapless Rebalance work? Swapless Rebalance closes or adjusts the old range and opens a new range without using any swaps. ## Swapless Rebalance Modes | Mode | Example | What it controls | | -------------- | --------------------------------------------- | ---------------------------------------------------------------- | | Fixed Schedule | Rebalance every 2 hours | Rebalances based on a schedule while avoiding swaps. | | Up or Down | Rebalance up or down after 10 minute cooldown | Lets the range follow price in both directions without swapping. | | Up only | Rebalance up after 10 minute cooldown | Lets the range follow upward price movement without swapping. | | Down only | Rebalance down after 10 minute cooldown | Lets the range follow downward price movement without swapping. | ## Swapless Rebalance Technical Customizations | UI field | Example | What it controls | | ------------------------------- | -------------------------------- | ---------------------------------------------------------------------------------------- | | Auto-Rebalance Deposit Slippage | Configured deposit slippage | Sets the slippage limit used when AR deposits into the new position. | | Liquidity Shape on Rebalance | Spot, Curve, Bid-Ask, Hybrid | Sets the liquidity shape used after the rebalance. | | AR Cooldown | Wait before AR can trigger again | Controls how soon Up or Down, Up only, or Down only can trigger again after a rebalance. |
How is Swapless Rebalance different from Swapped Rebalance? Swapless Rebalance moves the position range without performing a swap. Swapped Rebalance may use swaps during the rebalance process.
When does Rebalance Buffer apply? Rebalance Buffer applies to Swapless Fixed Schedule.
# Ping Pong Auto-rebalance Advanced swapless Auto-rebalance behavior for alternating range movement ## What is Ping Pong?
Ping Pong is a HawkFi Advanced swapless Auto-rebalance (AR) mode that alternates rebalance behavior between two configured directions or ranges. ## How does Ping Pong work? Ping Pong uses swapless Auto-rebalance (AR) to move the position between two configured sides instead of only following one continuous rebalance direction. Example: after one side of the setup is reached, HawkFi can move the range according to the next configured Ping Pong behavior. ## Ping Pong Customizations
CustomizationExampleWhat it controls
Total bins if AR down68 binsSets the total number of bins used when the position goes out of range below and AR down succeeds.
Spread0-bin spreadSets how far the new range is placed from the effective price after rebalance.
Total bins if AR up68 binsSets the total number of bins used when the position goes out of range above and AR up succeeds.
Ping Pong customizations should be filled from the current Ping Pong UI once the screenshot is added. ## FAQs for Ping Pong
How is Ping Pong different from swapped Auto-rebalance (AR) Swapped Auto-rebalance use swaps to match the required deposit ratio when moving the position range. Ping Pong uses swapless AR behavior and alternates the position range between two configured sides without swapping assets.
Is Ping Pong Swapless Auto-rebalance (AR) Yes. Ping Pong is an Advanced version of swapless Auto-rebalance (AR). It uses swapless rebalance mechanics, but adds the Ping Pong range logic for AR up and AR down behavior.
# Auto-compound (AC) Automatically reinvest earned fees or rewards back into your position ## What is Auto-compound (AC)?
Auto-compound (AC) is a HawkFi automation that automatically reinvests trading volume fees or rewards back into your position. ## How does Basic Auto-compound (AC) work? Auto-compound (AC) reinvests earned fees or rewards back into your liquidity position when the compounding condition is met. Example: when your earned $50 in fees, HawkFi will add back those fees back into the position instead of leaving them idle. ## Auto-compound (AC) Customizations | Customization | Example | What it controls | | --------------------------- | ------- | ------------------------------------------------------------------------------------------------------------ | | Liquidity shape on compound | Spot | Your compounded fees and rewards will be deposited equally to each price bin of your position's price range. | {% hint style="info" %} Liquidity shape on compound options are: Spot, Curve, Bid-Ask {% endhint %} ## How Auto-compound (AC) behaves per strategy | Strategy | How AC behaves | | ---------------- | -------------------------------------------------------------------------------- | | Precision Curve | Compounds earned fees back into the position while RL manages the Curve shape. | | Precision Hybrid | Compounds earned fees while Hybrid manages fee capture and swing style exposure. | | HFL | Compounds earned fees back into a high frequency LP position when enabled. | ## FAQs for Auto-compound (AC)
How is it different from Auto-accumulate Fees? Auto-compound (AC) adds earned fees or rewards back into the position. Auto-accumulate Fees (AA) claims fees into the selected token path instead. | Automation | What happens to fees | Best used when | | ------------------------- | --------------------------------------------------------- | ------------------------------------------------------------ | | Auto-compound (AC) | Fees or rewards are reinvested back into the LP position. | You want generated fees to keep working inside the position. | | Auto-accumulate Fees (AA) | Fees are claimed and converted in USDC or SOL | You want to separate fees earned from position. |
Does Auto-compound (AC) help better returns? Auto-compound (AC) applies the concept of compound interest by reinvesting earned fees or rewards back into the position, but returns still depend on market conditions, price movement, volume, and strategy setup.
# Auto-accumulate fees (AA) Automatically collect earned fees into your HawkFi wallet ## What is Auto-accumulate Fees (AA)?
Auto-accumulate Fees (AA) is a HawkFi automation that strategically lets you accumulate fees into your HawkFi wallet. ## How does Basic Auto-accumulate Fees (AA) work? Auto-accumulate Fees (AA) claims earned fees and swaps them into the selected token when the accumulation condition is met. Example: when your position earns $50 in fees, HawkFi will claim and swap those fees to SOL or USDC in your HawkFi wallet instead of adding them back into the position. ## Auto-accumulate Fees (AA) Customizations | Customization | What it Controls | | ---------------------- | ----------------------------------------------------------------------------------------- | | Claim and Swap to SOL | Automatically claim fees and swap to SOL, which you can then claim in Your HawkFi Wallet | | Claim and Swap to USDC | Automatically claim fees and swap to USDC, which you can then claim in Your HawkFi Wallet | ## How Auto-accumulate Fees (AA) behaves per strategy | Strategy | How AA behaves | Goal | | -------- | ---------------------------------------------------------------------------- | -------------------------------------------------------------- | | HFL | Claims and swaps earned fees from the concentrated LP position when enabled. | Accumulate fees separately from a concentrated range strategy. | ## FAQs for Auto-accumulate Fees (AA)
How is it different from Auto-compound (AC)? Auto-accumulate Fees (AA) claims and swaps earned fees into your HawkFi wallet. Auto-compound (AC) adds earned fees or rewards back into the position instead. | Automation | What happens to the Fees | Best used when | | ------------------------- | --------------------------------------------------------- | ------------------------------------------------------------ | | Auto-accumulate Fees (AA) | Fees or rewards are reinvested back into the LP position. | You want to separate fees earned from position. | | Auto-compound (AC) | Fees are claimed and converted in USDC or SOL | You want generated fees to keep working inside the position. |
Does Auto-accumulate Fees help you profit? Sort of. Auto-accumulate Fees can act like automated fee taking because it secures earned fees and redirects them into your HawkFi wallet, but market conditions, price movement, volume, and strategy setup still matter.
# Take Profit (TP) Automatically close your position when your profit target is reached ## What is Take Profit (TP)?
Take Profit (TP) is a HawkFi automation that automatically closes your position once a specific profit target is reached. ## How does Basic Take Profit (TP) work? Take Profit (TP) monitors your selected trigger and closes the position when the configured profit condition is met. Example: if your Pool Price TP Trigger is reached, HawkFi 100 percent of assets, claim fees and rewards, close the position, and send the assets to your HawkFi wallet. ## Take Profit (TP) Customizations Take Profit settings define the trigger, slippage, and asset handling after the position closes. ### TP Trigger Customizations: | TP Trigger | Example | What it controls | | ------------------------ | ------------------------------ | --------------------------------------------------------------------------------------------- | | Pool price | Pool price reaches 0.08 | Triggers TP when the pool price reaches the configured target. | | Position balance | Position value reaches $1,000 | Triggers TP when the position balance reaches the configured value. | | Unclaimed fees | Unclaimed fees reach $50 | Triggers TP when unclaimed fees reach the configured value. | | Balance + unclaimed fees | Combined value reaches $1,050 | Triggers TP when the combined position balance and unclaimed fees reach the configured value. | | Market cap | Token Market cap reaches $10M | Triggers TP when Token market cap reaches the configured target. | | Position age | Position closes after 24 hours | Triggers TP when the position has met configured amount of time. | | PnL (USD) | USD PnL reaches 7% | Triggers TP when position PnL reaches the configured positive percentage measured in USD. | | PnL (SOL) | SOL PnL reaches 7% | Triggers TP when position PnL reaches the configured positive percentage measured in SOL. | {% hint style="info" %} When a USD or SOL PnL trigger is saved in a custom model, HawkFi keeps the configured percentage and calculates the position-specific target from the deposit when the model is applied. {% endhint %} ### TP Output Customizations: | TP output | Example | What it controls | | ------------ | ---------------------- | ------------------------------------------------------------------------------------- | | No Swap | Keep assets as-is | Closes the position and sends the assets to your HawkFi wallet without swapping them. | | Swap to SOL | Convert assets to SOL | Closes the position, swaps the assets to SOL, and sends them to your HawkFi wallet. | | Swap to USDC | Convert assets to USDC | Closes the position, swaps the assets to USDC, and sends them to your HawkFi wallet. | ### TP Technical Customizations: | Customization | | | -------------------- | ---------------------------------------------------------------------------------------- | | TP Trigger | Selects which condition HawkFi watches to decide when Take Profit should execute. | | Take Profit Slippage | Sets the slippage limit used when TP closes the position and performs any selected swap. | {% hint style="info" %} When TP is triggered, HawkFi withdraws 100 percent of assets, claims fees and rewards, and closes the position. Rent is refunded to the connected wallet. {% endhint %} ## How Take Profit (TP) behaves per strategy | Strategy | How TP behaves | Goal | | ------------ | -------------------------------------------------- | ---------------------------------------------------- | | Heart Attack | Closes the position when the position is 7% in PnL | Lock in gains from a quick-fee genearation position. | ## FAQs for Take Profit (TP)
Does Take Profit guarantee profit? Take Profit helps you automate your exit when your configured profit condition is reached, and helps you secure profit.
How is it different from Auto-accumulate Fees (AA)? Take Profit is for closing the full position after a target is reached. Auto-accumulate Fees is for keeping the position open while collecting earned fees into your HawkFi wallet. Use Take Profit when the goal is to exit. Use Auto-accumulate Fees when the goal is to keep LPing while separating fees earned from the position.
# Stop Loss (SL) Automatically close your position when your downside condition is reached ## What is Stop Loss (SL)?
Stop Loss (SL) is a HawkFi automation for risk management that automatically closes your position to prevent further losses once a specific price level is reached ## How does Basic Stop Loss (SL) work? Stop Loss (SL) monitors your selected trigger and closes the position when the configured downside condition is met. ## Stop Loss (SL) Customizations Take Profit settings define the trigger, slippage, and asset handling after the position closes. ### SL Trigger Customizations | UI field | Example | What it controls | | ------------------------ | -------------------------------------------------- | --------------------------------------------------------------------------------------------- | | Pool price | Pool price falls to 0.05 | Triggers SL when the pool price reaches the configured loss target. | | Position balance | Position value falls to $700 | Triggers SL when the position balance reaches the configured value. | | Unclaimed fees | Unclaimed fees fall below the configured threshold | Triggers SL when unclaimed fees reach the configured value. | | Balance + unclaimed fees | Combined value falls to $750 | Triggers SL when the combined position balance and unclaimed fees reach the configured value. | | Market cap | Market cap falls to $350K | Triggers SL when market cap reaches the configured loss target. | | Position age | Position closes after 3 hours | Triggers SL when the position has met configured amount of time. | | PnL (USD) | USD PnL reaches -20% | Triggers SL when position PnL reaches the configured negative percentage measured in USD. | | PnL (SOL) | SOL PnL reaches -20% | Triggers SL when position PnL reaches the configured negative percentage measured in SOL. | {% hint style="info" %} When a USD or SOL PnL trigger is saved in a custom model, HawkFi keeps the configured percentage and calculates the position-specific target from the deposit when the model is applied. {% endhint %} ### SL Output Customizations | UI field | Example | What it controls | | ------------ | -------------------------------- | ------------------------------------------------------------------------------------- | | No Swap | Keep assets as-is | Closes the position and sends the assets to your HawkFi wallet without swapping them. | | Swap to SOL | Convert withdrawn assets to SOL | Closes the position, swaps the assets to SOL, and sends them to your HawkFi wallet. | | Swap to USDC | Convert withdrawn assets to USDC | Closes the position, swaps the assets to USDC, and sends them to your HawkFi wallet. | ### SL Technical Customizations | UI field | Example | What it controls | | ------------------ | ------------------ | ---------------------------------------------------------------------------------------- | | SL Trigger | Pool price | Selects which condition HawkFi watches to decide when Stop Loss should execute. | | Stop Loss Slippage | Fixed at 3 percent | Sets the slippage limit used when SL closes the position and performs any selected swap. | ## How Stop Loss (SL) behaves per strategy | Strategy | How SL behaves | Goal | | ------------ | ------------------------------------------------------ | --------------------------------- | | Heart Attack | Closes the position when the position reaches -20% PnL | Exit when the SL rule is reached. | ## FAQs for Stop Loss (SL)
Does Stop Loss remove market risk? Stop Loss helps automate your exit when your configured downside condition is reached. It does not remove market risk, but it helps execute risk-management to close once your SL rule is hit.
How is it different from Take Profit (TP)? Take Profit closes the position when an upside target is reached. Stop Loss closes the position when a downside condition is reached. Both use similar trigger, output, and technical settings. The main difference is the intent of the exit.
# Understand Fees and Risks Review the fee source and the main risks for HawkFi Models, Agents, and Laboratory before using live capital. HawkFi Models, HawkFi Agents, and HawkFi Laboratory do different jobs. Their fees and risks should be read in the context of the workflow you plan to use. ## Find the current fee source | Workflow | Read this before funding | | ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Core HawkFi LP positions and Models | [HawkFi fee FAQ](/whitepaper/guides-and-support/faqs#what-are-the-fees-related-to-using-hawkfi-what-is-a-yield-performance-fee) | | Market Making Agent | [Market Making Agent fee table](/whitepaper/market-making-agent/market-making-agents-mma#fees) | | Screener Agent with Osprey | Review Agent funding, fixed position size, position management, and exit settings in the [Screener Agent guide](/whitepaper/lp-screener-agent/screener-agents-osprey-v1). | | Osprey Trading Agent | Each swap charges `1%`: entry deducts it from gross WSOL input, while exit deducts it from gross WSOL output before net proceeds are credited. Review the [Osprey Trading Agent fee details](/whitepaper/trading-agent/osprey-trading-agent#fees). | | HawkFi Laboratory | Laboratory is for simulation. Review live fees on the workflow you choose after the backtest. | {% hint style="info" %} Always review the current product page before funding. Market Making Agent fee tiers and access status belong in the Market Making Agent reference. {% endhint %} ## Know the main risks | Risk | Where it matters | What to check | | ---------------------------------------- | --------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | | Market and price risk | Every live workflow | The asset can move against the setup. HawkFi does not guarantee future returns. | | Impermanent loss | Liquidity Providing and Screener Agent LP positions | Compare fees and PnL with Pair HODL, Manual LP, token inventory, and drawdown. | | Adverse selection and toxic fills | Market Making Agent | Check markout, momentum, quote distance, fill quality, and whether quotes are too aggressive. | | Inventory drift | Market Making Agent and LP positions | Check the ending token mix, inventory skew, TVL breakdown, and whether PnL came with unwanted exposure. | | Model mismatch | Models and Agents | A model optimized for one asset class or market regime may not fit another. Test the pool and market window first. | | Selectivity and opportunity frequency | Screener Agent with Osprey | A selective screening model may wait instead of opening constant positions. A broader model can increase activity and risk. | | Direct token exposure and swap execution | Osprey Trading Agent | Review the token filters, entry size, total allocation, slippage, TP/SL, maximum hold, and the fee charged on each swap leg. | | Backtest overconfidence | HawkFi Laboratory | Historical results are research. They do not predict future returns or remove live execution differences. | | Network and funding limits | Live Agents and LP positions | Keep enough SOL for the workflow and review priority fee settings when transactions fail. | ## Before using live capital 1. Choose the workflow and open its current fee source. 2. Decide which market, inventory, and drawdown risks you can monitor. 3. Test the configuration in HawkFi Laboratory when the mode is available. 4. Fund an amount that matches the risk you are prepared to manage. 5. Define what would make you pause, change, or exit the setup. ## Go deeper * [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent) * [Fund Your Agent Wallet](/whitepaper/start-here/fund-your-agent-wallet) * [Move from Backtest to Live](/whitepaper/hawkfi-laboratory/move-from-backtest-to-live) * [Reduce Impermanent Loss](/whitepaper/learn-hawkfi/how-to-reduce-il) * [Solve Common Problems](/whitepaper/guides-and-support/faqs) # FAQs ### What are the fees related to using Hawkfi? / What is a yield performance fee? HawkFi charges: * 0% deposit/withdrawal fees * 0% automation fees * 8% on the yield only, not initial deposit (so if you generate $1 in fees, HawkFi charges $0.08) * Other liquidity managers charge 9-25% of yield, plus 0.1% withdrawal fee on initial capital * HawkFi covers DEX pool creation & bin initialization fees for users ### Why are STAs needed? Storage Token Accounts (STAs) are what we call Token Specific Program Derived Accounts that are necessary to implement the automations we perform on your behalf as you use Hawkfi. STAs are needed so we ensure that tokens from positions you’ve closed via Take Profits or Stop Losses, earned from existing positions but would not want to be compounded, are kept untouched by other automations that are running on the other positions you have active on Hawkfi. ### Why am I not able to deposit/open a position? * You may be encountering a number of issues, or the network may be congested if you are unable to open a position on Hawkfi. * Try the following steps if you are unable to open a position on Hawkfi: 1. Check if you have enough SOL to open a position 2. Increase the priority fee multiplier 3. Increase the priority fee cap 4. Check if you have enough SOL to pay for the increased priority fees ### Why am I not able to Withdraw or Claim? * You may be encountering a number of issues, or the network may be congested if you are unable to open a position on Hawkfi. * Try the following steps if you are unable to open a position on Hawkfi: 1. Check if you are trying to claim a scam token * A scam token is a token that shares the same ticker, but has a different mint than recently traded tokens that aims to trick you to buy more tokens but cannot be sold 2. Increase the priority fee multiplier 3. Increase the priority fee cap 4. Check if you have enough SOL to pay for the increased priority fees ### Why am I not able to claim some tokens I see on the HawkFi wallet? We’re seeing a number of cases where scammers airdrop tokens to Hawkfi Wallets. You will not be able to claim these tokens as the required token accounts to claim these tokens have not been opened. Check if you are trying to claim a scam token A scam token is a token that shares the same ticker, but has a different mint than recently traded tokens that aims to trick you to buy more tokens but cannot be sold ### Why are my positions not being automated? or Why are there delays in my position’s automations? 1. Your slippage might be too tight 2. The network may be congested ### Why did my position get rebalanced? 1. Rebalances are performed based on a target price or condition which you have set. The target price is based on the price of the pool where your liquidity is in, and not on the overall market price. Once the target price is reached, we perform a rebalance on your position. 2. If you believe the target price or trigger has not been reached but a rebalance has been executed, verify the case by doing: 1. Navigate to the Analytics tab of your Position 2. Click the Birdeye link in the Pool page where your position is located 3. Compare the Price in which your position was rebalanced ### Why did my Take Profit or Stop Loss not fire? Limit Orders (Take Profits and Stop Losses) are performed based on a target price or condition which you have set. The target price is based on the price of the pool where your liquidity is in, and not on the overall market price. Once the target price is reached, we perform a Limit Order and close your position. If you believe the target price or trigger has not been reached but a Limit Order was not executed, verify the case by doing: Navigate to the Analytics tab of your Position Click the Birdeye link in the Pool page where your position is located Compare the timestamp in which your position should have been closed. ### It says I earned X amount, but my position is only worth Y. Where did my fees go? Fees earned by user’s positions may have been claimed by the user, compounded by Hawkfi, or claimed during a rebalance. The fees are added into the position during compounds or rebalances (if compounds are enabled). If any of the tokens trend downwards, rebalanced, trend upwards, and rebalanced again, the fees earned would have been used to offset any losses incurred during the price swings of the paired tokens. ### How can a pool get listed on HawkFi? Hawkfi automatically lists liquidity pools created on Meteora. Just create your desired pool on Meteora, and Hawkfi picks it up! What are HFI Points? How can I earn them? Are they live? ### How can we export the HFI wallet to claim airdrops that the wallet may be entitled to? You will not be able to export the HFI wallet since it is a program derived address (PDA) which can only be used within the Hawkfi smart contract. ### Why am I earning less fees than the stated APR when I entered? The APRs displayed are based on the volume from the past 24 hours. They are not meant to be used as predictors of future gains or fee earnings from the pool. The displayed APRs are only meant to show the returns of the pool from the past 24H. # Referral Program ### HawkFi Referral Program HawkFi referral codes live inside the connected wallet menu. Connect your wallet, open the wallet dropdown, then choose `Referral` to view your referral code. * **Share your referral code**: Copy your code from the `Referral` flyout and share it with friends or communities. * **Use a referral code**: If you receive a HawkFi referral code, enter it through the same referral flow after connecting your wallet.
{% hint style="info" %} The old standalone HFI points pill is no longer shown in the main navigation. Referral access now starts from the wallet dropdown. {% endhint %} # HawkFi vs Manual LP If you already know how to LP, HawkFi MAXIMIZES your fees & trading gains for you Understand how HawkFi **dominates fees & swing trading gains over manual liquidity providers**, with high-frequency alpha strategies ### At a glance
HawkFiManual LP
Fee concentrationUp to 7x more fees (HFL), or 2x more fees (Precision) with high frequency rebalance/reshape1x baseline fee
RebalancingAlways in-range to generate fees, with 0-minute rebalancesManual wallet interactions to constantly rebalance or miss out on fees
Liquidity shapeMaximize fee capture with high-frequency liquidity reshapes to concentrate capital around active binsStatic shape — drifts away from active bin as price moves, reducing fee efficiency
⭐️ Bin initialization feesFree — covered by HawkFiPaid by you on every new position
Fee compoundingAuto-compound (AC) reinvests fees to grow your position and accelerate returnsManual claim, manual re-deposit — fees sit idle until you act
Strategy per market conditionDedicated strategies for high-volume, high-volatility, and mixed markets — every condition has a playbookOne static setup regardless of whether the market is trending, ranging, or volatile
Risk managementBuilt-in Stop Loss (SL) and Take Profit (TP) — downside protection and earnings targets on autopilotManual monitoring; you need to be watching to react
### Targeted strategies for every Market Scenario
MarketHawkFiManual LP
High volume

Price trending up		HFL — always in-range with >7x fee concentration; captures every move on the way upManually rebalance to chase price; miss fees during every gap
High volume

Price sideways		Precision Curve — RL reshapes liquidity to print ~2x more fees across the same rangeStatic shape earns baseline fees; liquidity drifts from optimal distribution
High volatilityPrecision Hybrid — prints stable fees + captures swing trading gains in one positionOne static setup; zero swing capture, zero adaptability
Price correction / dipPrecision Curve (single-side SOL) or Precision Hybrid — stays active, positioned for the recoveryLikely out of range, earning zero fees while you wait
### Build your own strategy, with smart & high-performance machine execution
Smart automationDescription
Auto-compound (AC)Fees automatically reinvested → position grows, returns compound
Auto-accumulate SOL (AA)Fees claimed and converted to SOL → protects against token price decline
Auto-rebalance (AR)

Swap or Swapless		0-minute rebalances to stay in-range continuously. Configurable: swapless or swapped, Ping Pong (follow active bin), directional (up-only, down-only, or both), custom range width after rebalance
Reshape Liquidity (RL)High-frequency reshaping of your liquidity curve around the active bin. Configurable trigger: every 1–69 bins of price movement
Liquidity shapeChoose Spot, Curve, Bid-ask, or Hybrid (50/50 Spot + Bid-ask) per strategy
Take Profit (TP)Position closes and converts to SOL or USDC at your target price/balance/pnl/etc
Stop Loss (SL)Position closes and converts to SOLor USDC at your stop price — downside protection without manual monitoring
# How to reduce IL High Frequency LP gives turbo fee-generation, but there is always Impermanent Loss (IL), and there is no avoiding it in liquidity providing. The goal is to OUTPRINT IL, while mitigating IL. Here’s how: 1. **Wider LP ranges** * High Frequency Liquidity prints hard from tight real-time rebalancing LPs. You can mitigate IL by setting slightly wider ranges. Tradeoff is less concentrated (but possibly more sustainable) fee generation. * :bulb:Alpha: Set LP widths based on expected volatility of token * :bulb:Alpha: Slow weekends with muted price action are great for HFL 2. **Slower auto-rebalances** * 0 minute real-time rebalances maximize in-range fee generation, especially for high vol pools. But sometimes you can set 5-15 minute rebalances instead to avoid adverse IL from extreme pumps/dumps Tradeoff is less in-range (but possibly more sustainable) fee generation
3. **Directional auto-rebalances** * Set HawkFi to rebalance when token price goes up-only, instead of up & down. Rebalances amplify positive IL upwards, and negative IL downwards. * Tradeoff is significantly less fee generation, but up-only rebalances are suitable for steady long-term fee generation of high-conviction tokens
4. **Strict Entries & Exits** * Only enter LPs when A) Token price trades sideways/upwards, and B) Volume is high * Avoid & immediately exit when A) Token price dumps, or B) Volume dries up 5. Set Stop Loss at lower bounds of LP price range
# Use HawkFi Docs with AI Give ChatGPT, Claude, or another AI system direct access to HawkFi's canonical public documentation. HawkFi keeps one public documentation source for people and AI systems. The task guides help readers start quickly. The detailed Models, Agents, Laboratory, automation, fee, and risk pages remain the canonical reference when a question needs more depth. ## Choose an access method | Use case | Open | | ----------------------------------------------- | -------------------------------------------------------------------- | | Browse as a person | [HawkFi GitBook](https://hawkfi.gitbook.io/whitepaper) | | Give an AI system the documentation index | [llms.txt](https://hawkfi.gitbook.io/whitepaper/llms.txt) | | Give an AI system the full documentation corpus | [llms-full.txt](https://hawkfi.gitbook.io/whitepaper/llms-full.txt) | | Connect an MCP-compatible AI client | `https://hawkfi.gitbook.io/whitepaper/~gitbook/mcp` | | Give an AI one exact source | Open the relevant GitBook page and add `.md` to its public page URL. | {% hint style="info" %} Use `llms.txt` for routing. Use `llms-full.txt` when the AI needs the full corpus. Use an exact page when you want the narrowest source for a specific question. {% endhint %} ## Route the question to the right source | Question | Start with | | ---------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- | | Which live Agent should I use? | [Choose Your HawkFi Agent](/whitepaper/start-here/choose-your-hawkfi-agent) | | How does Market Making Agent work? | [Market Making Agent](/whitepaper/market-making-agent/market-making-agents-mma) | | What does Osprey do? | [Screener Agent and Osprey V2](/whitepaper/lp-screener-agent/screener-agents-osprey-v1) | | How does Osprey Trading Agent work? | [Osprey Trading Agent](/whitepaper/trading-agent/osprey-trading-agent) | | Which Market Making Agent execution model should I choose? | [Market Making Agent Execution Models](/whitepaper/market-making-agent/market-making-agents-mma/execution-models) | | How do HawkFi LP models work? | [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) | | How do I test a setup? | [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) | | What are the current fees or main risks? | [Understand Fees and Risks](/whitepaper/guides-and-support/understand-fees-and-risks) | ## Prompt an AI system Copy this instruction when you want an AI system to answer from HawkFi's source of truth: ``` Use HawkFi's public GitBook as the canonical source. Start with its llms.txt index, then open the exact Markdown pages needed for the question. Distinguish HawkFi Agents, HawkFi Models, and HawkFi Laboratory. Treat Market Making Agent, Screener Agent, and Osprey Trading Agent as the three HawkFi Agent types. Treat Osprey as the screening agent or screening model used by both Screener Agent and Osprey Trading Agent, while keeping their LP and token-trading workflows separate. Treat Falcon as an execution model and Laboratory as simulation rather than live execution. Cite the exact HawkFi documentation pages used. If the docs do not answer something, say what is missing instead of guessing. ``` ## Keep retrieval reliable 1. Prefer the current GitBook page over old screenshots, posts, or copied notes. 2. Use the canonical product page for definitions and exact settings. 3. Use task pages for the sequence of actions. 4. Check dated benchmarks and beta status before repeating performance claims. 5. Treat Models, Agents, and Laboratory as the HawkFi core product suite. Treat Magpi as a different product under HawkFi. ## Documentation map * [HawkFi | Agent Terminal](/whitepaper) * [HawkFi Agents](/whitepaper/hawkfi-agents/hawkfi-agents) * [HawkFi Laboratory](/whitepaper/hawkfi-laboratory/hawkfi-laboratory) * [HawkFi Models](/whitepaper/models-and-automations-library/hawkfi-models) * [Tutorial Library](/whitepaper/start-here/tutorials)