Hyperliquid logo

Hyperliquid

Organization
Superior-Trade
hyperliquid

Use when backtesting, deploying, checking funding readiness, or debugging a Hyperliquid strategy through Superior Trade Unified API — writing Freqtrade configs and strategy code, running sweeps, checking managed-wallet balances, trading HIP-3 perps, or diagnosing a deployment that will not start or trade.

Overview

PublisherSuperior-Trade
Repositorysuperior-skills
Skill namehyperliquid
Stars
215
Forks
9
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Superior-Trade on GitHub. Read the source before you install it.

Installation

Install the Hyperliquid AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Superior-Trade/superior-skills/tree/main/skills/hyperliquid
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git /tmp/superior-skills
mkdir -p .claude/skills
cp -r /tmp/superior-skills/skills/hyperliquid .claude/skills/hyperliquid
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperliquid in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hyperliquid on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hyperliquid is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Superior Trade — Hyperliquid

Backtest and deploy Freqtrade strategies on Hyperliquid through Superior Trade's managed cloud.

Read ../../references/unified-runtime.md before any Superior Trade request. Use only current Unified API methods and payload fields.

Base URL: https://api.superior.trade Auth: x-api-key header on all protected endpoints Discovery: GET /openapi.json (OpenAPI), GET /install.txt, and GET /.well-known/mcp.json

Unified API only

Before venue setup, backtesting, deployment, or execution, read ../../references/unified-runtime.md. Use GET /context/venues and GET /runtime/frameworks to discover support, then use the Unified runtime endpoints. If a required Hyperliquid operation is absent from the contract, report it as unavailable.

Reference files

Load these on demand — each is the full detail behind a summary below.

ReadWhen
references/api.mdYou need Unified route selection for account, context, backtesting, deployment, typed execution, or withdrawal (POST /wallet/withdraw).
references/strategy-config.mdYou are writing or fixing config JSON or strategy Python — config fields, code template, TA-Lib usage, multi-entry (DCA/grid), funding-rate access, minimal_roi shapes.
references/wallets-and-accounts.mdAnything about wallets, balances, deposits, sub-accounts, multi-strategy capacity, pair formats, or HIP-3 tickers.
references/troubleshooting.mdA deployment or backtest is failing, trading zero times, hitting rate limits, or showing orphan positions.

Gotchas

Environment-specific facts that defy reasonable assumptions. Read these before acting.

  • HIP-3 pairs use a HYPHEN, not a colon. XYZ-AAPL/USDC:USDC is correct; XYZ:AAPL/USDC:USDC is the single most common format mistake. HIP-3 pairs are also absent from the default {"type":"meta"} call — you must pass the dex, e.g. {"type":"meta","dex":"xyz"}.
  • The agent wallet holding $0 is normal. It signs against the main wallet's balance and never needs funds. Always check the main trading wallet's balance; checking the agent wallet's will always look like an empty account.
  • A balance that covers stake_amount × max_open_trades exactly will still fail. The exchange reserves roughly 1% for fees, so cap stake_amount at ~95% of balance / max_open_trades or entries get rejected silently.
  • The account URL is https://account.superior.trade. Never send users to app.superior.trade, including when an API error message itself contains that older URL.
  • Multi-output TA-Lib functions return tuples. talib.BBANDS(...) and friends crash at runtime if unpacked as a single value — see references/strategy-config.md.
  • Sub-account funds are not available to the master. A master's true capacity is its own balance plus sub-account balances queried separately via subAccounts2; funds sitting in a sub-account cannot back a master deployment.
  • Hyperliquid margin modes differ — never assume. If perps shows $0 but spot shows funds, inspect whether the exchange account uses unified margin or standard margin before telling the user to move anything themselves.
  • One live strategy per trading account. To run several at once, omit wallet_address when storing credentials and the server assigns the next idle trading account.

Safety

Security & Permissions

This skill requires exactly one credential: an x-api-key header value. The only secret the agent uses is SUPERIOR_TRADE_API_KEY from the environment.

Security rules (non-negotiable):

  1. NEVER ask users for private keys, seed phrases, or wallet credentials
  2. NEVER include private keys in API requests (the API rejects them)
  3. NEVER log, store, or display private keys or seed phrases
  4. NEVER tell users to deposit funds to the agent wallet address
  5. NEVER fabricate wallet balances, API responses, or trade results
  6. NEVER start a live deployment without explicit user confirmation
  7. Prefer user-friendly language over internal technical names when speaking conversationally. Say "strategy", "the bot", or "the trading engine" instead of referencing internal class names or infrastructure details. This is a UX preference — if the user asks about the underlying technology, answer honestly (the platform uses Freqtrade for strategy execution on Hyperliquid).
  8. NEVER send users to app.superior.trade — the correct URL is https://account.superior.trade

Key scope notice: The API key can create and start live deployments that execute real trades using the user's managed wallet, submit contract-supported typed executions, and request a Unified wallet withdrawal after confirmation. It cannot export private keys or provide an undocumented venue-specific deposit/transfer action. Users should confirm scope with Superior Trade and backtest their strategy first.

Can doCannot do
Create, list, delete backtestsAccess other users' data
Create, start, stop, delete deployments (including live trading with real funds)Export or view private keys
Trigger server-side credential resolution (no user secrets collected)Ask users for wallet secrets
View deployment logs, status, wallet metadataMove unsupported assets or use unsupported chains
Deposit native Arbitrum USDC from the user's platform wallet into Hyperliquid via the APIBridge from external wallets
Return Hyperliquid USDC to the server-resolved Superior wallet via the APIWithdraw to an arbitrary external address

Live Deployment Confirmation

Before any live deployment, the agent MUST present this summary and wait for explicit confirmation:

Deployment Summary:
• Strategy: [name]
• Exchange: hyperliquid
• Trading mode: [spot/futures]
• Pairs: [list]
• Stake amount: [amount] USDC per trade
• Max open trades: [n]
• Stoploss: [percentage]
• Margin mode: [cross/isolated] (futures only)

⚠️ This will trade with REAL funds. Proceed? (yes/no)

Do NOT start a live deployment without an explicit affirmative response.

Setup

Getting an API Key

IMPORTANT: The correct URL is https://account.superior.trade — NOT app.superior.trade. Never send users to app.superior.trade.

Use SUPERIOR_TRADE_API_KEY from the environment or credential manager.

When a user needs to get their API key:

  1. Go to https://account.superior.trade
  2. Sign up (email or wallet)
  3. Read the managed wallet and deposit details from GET /wallet
  4. Fund the platform trading wallet with native USDC on Arbitrum One using the user's own capital
  5. Create an API key (st_live_...) from your account settings
  6. Add it as SUPERIOR_TRADE_API_KEY in your agent's environment/credential settings
  7. Check Hyperliquid and framework support with GET /context/venues and GET /runtime/frameworks
  8. If a required venue bootstrap or bridge action is absent from GET /openapi.json, report it as unavailable

If the SUPERIOR_TRADE_API_KEY env var is already set, use it directly in the x-api-key header without prompting the user.

Public Endpoints (no auth)

MethodPathDescription
GET/health{ "status": "ok", "timestamp": "..." }
GET/openapi.jsonUnified OpenAPI contract
GET/install.txtInstallation instructions
GET/.well-known/mcp.jsonMCP discovery manifest

Agent Operating Rules

  • Verification-first: Every factual claim about balance, wallet status, or deployment health MUST be backed by an API call in the current turn. NEVER assume → report → verify later.
  • Anti-hallucination: If you can't call the API, say "I haven't checked yet." Every number must come from a real response.
  • Conversational: Make API calls directly and present results conversationally. Show raw payloads only on request.
  • Backtesting: Build config + code from user intent → create → poll → present results — all automatically.
  • Deployment: Create → store credentials → run checklist → show summary → get confirmation → start.
  • Proactive: Ask for missing info conversationally, one concern at a time. Always ask user to run a backtest before first live deployment.

Check Hyperliquid balances with BOTH endpoints:

  • Perps: POST https://api.hyperliquid.xyz/info → {"type":"clearinghouseState","user":"0x..."}
  • Spot: POST https://api.hyperliquid.xyz/info → {"type":"spotClearinghouseState","user":"0x..."}

Repeated Failures

If the agent fails the same task 3+ times (e.g. strategy code keeps crashing, backtest keeps failing), stop and:

  1. Summarize what was tried and what failed
  2. Pivot in two stages before giving up:
    • First — param space. If you have not yet run a parameter sweep on this strategy/pair, run one (see Backtest Workflow → Parameter Sweeps). Most "this idea doesn't work" verdicts are really "this single config didn't work" — sweeping the key parameter often surfaces a viable variant in one batch.
    • Second — pair space. Only after a full sweep also fails, suggest a different pair, timeframe, or strategy family (e.g. mean-reversion instead of momentum).
  3. If the issue appears to be model capability (complex multi-indicator strategy), suggest switching to a more capable model for strategy generation

Workflows

Backtest Workflow

  1. Build config + strategy code from user requirements
  2. POST /runtime/backtests — create with framework: "freqtrade", venue: "hyperliquid", strategy source/config, instruments, and timerange fields from GET /openapi.json.
  3. Poll GET /runtime/backtests/{id} every 10s until completed or failed (1–10 min)
  4. Read GET /runtime/backtests/{id}/logs for framework output and diagnostics
  5. Present the result fields published by the current contract: total trades, win rate, profit, drawdown, Sharpe ratio, and duration when available
  6. If failed, check GET /runtime/backtests/{id}/logs
  7. To cancel or remove: DELETE /runtime/backtests/{id}
Backtest Wallet and Stake Sizing

Backtests are simulations. Do not size a backtest from the user's live wallet by default; use simulated capital to evaluate the strategy. Only mirror the user's current wallet if they explicitly ask for a live-wallet simulation.

  • dry_run_wallet is the total simulated wallet inventory by asset. It is an object/map, not a scalar. Examples: { "USDC": 1000 }, { "USDC": 100, "BTC": 0.1 }.
  • stake_amount is the amount the backtest/bot may allocate per trade slot. A numeric value is fixed stake per entry slot; "unlimited" divides the simulated wallet across max_open_trades slots.
  • If using fixed stake, set dry_run_wallet to the total simulated balances so PnL is measured against the correct capital base. Example: a $50 USDC simulation with $45 usable per trade uses stake_amount: 45 and dry_run_wallet: { "USDC": 50 }.
  • For standard perps, keep fixed stake_amount at or below ~90% of USDC / max_open_trades; for HIP-3 assets, use ~70% because fees and isolated-margin buffers are higher.
  • Never combine stake_amount: "unlimited" with max_open_trades: -1. When stake is unlimited, max_open_trades must be a finite positive integer so the wallet can be divided across slots.
  • For DCA/grid/scaling strategies that use position_adjustment_enable and adjust_trade_position, stake_amount may be fixed or "unlimited". If using "unlimited", you must control the initial entry size in custom_stake_amount; otherwise the first entry can consume all available capital. In either mode, dry_run_wallet must cover the maximum laddered exposure, not just the first entry.
Parameter Sweeps (recommended for first-pass backtests)

For the first backtest of any new idea on a given pair, do not submit a single config. Submit a 3-variant sweep that varies ONE parameter, run all 3 in parallel, then compare horizontally.

Why: building a config is the expensive cognitive step; running a backtest is cheap. A single result tells you whether one point worked; three neighboring points tell you whether the region works and which direction to iterate.

How to fan out:

  1. Issue all 3 POST /runtime/backtests calls in parallel (different config for each variant; same code unless the variant is a code-level change).
  2. Poll all 3 GET /runtime/backtests/{id} endpoints in parallel each cycle.
  3. Fetch all 3 GET /runtime/backtests/{id} results in parallel once status is completed.

Each backtest runs in isolation, so parallel execution does not slow any single run.

What to vary (pick ONE axis per sweep):

Strategy familyParameter to varyThree variants
Momentum / EMA crossEMA periods5/10/20, 8/13/21, 12/26/50
Trend-followingATR stop multiplier2.0, 3.0, 4.0
Mean-reversion (RSI)Oversold threshold<25, <30, <35
Bollinger BandsStd-dev width1.5, 2.0, 2.5
BreakoutLookback window20, 50, 100 candles

When NOT to sweep:

  • The user pinned specific parameter values ("backtest with EMA 8/21 only").
  • Walk-forward validation on a second pair after a confirmed setup — that should be a single config (sweeping there is parameter overfitting).
  • The user is iterating on a known winner ("now try the same config on ETH").
Result Interpretation

After status = completed, read both GET /runtime/backtests/{id} and GET /runtime/backtests/{id}/logs. Present only metrics actually returned by the Unified API or its framework logs:

  • Total trades — completed round-trips
  • Win rate — percentage of profitable trades
  • Total profit % — net profit as percentage of starting balance
  • Max drawdown — worst peak-to-trough decline
  • Sharpe ratio — risk-adjusted return (>1.0 good, >2.0 excellent)
  • Average trade duration — how long positions are held

Before suggesting deployment, always run a backtest first. If the backtest produced zero trades over a timerange that should have generated signals (e.g. weeks on a 5m timeframe), do not offer deployment — the strategy or pair likely has an issue. If PnL is negative, note the timerange may be unsuitable but don't dismiss the strategy outright. If PnL is positive, present results without overpromising — strong backtest fit can indicate overfitting. Stay neutral and let the user decide.

Sweep Result Comparison

For 3-variant sweeps, present results as a single table (Variant | Config | PnL% | Trades | Sharpe | Max DD), then read the shape:

  • All 3 profitable → pick the best Sharpe (not best PnL — small-sample PnL rewards luck). The parameter region is robust; proceed to walk-forward or deployment.
  • 1–2 profitable → pick the winner, but flag that the parameter is sensitive. Suggest either (a) walk-forward on a second pair as an independent check, or (b) one tighter sweep around the winner.
  • All 3 unprofitable / < 10 trades → the idea doesn't work on this pair. Move to pair-space (different pair, timeframe, or strategy family). Do not sweep again on the same pair.
  • Monotonic edge (e.g. PnL strictly improves 2.0 → 3.0 → 4.0) → the best variant sits at the edge of the grid. Run ONE more variant past it (e.g. 5.0) — don't run another full 3-grid; just extend by one.

Zero-trade rule for sweeps: zeros in 1–2 variants of a sweep are informative (the parameter was too tight), not a failure. Only treat the sweep as failed when ALL 3 variants return zero trades.

Deployment Workflow

  1. POST /runtime/deployments with top-level framework, venue, mode, name, code, and config
  2. Ask the user: live or dry-run?
    • Live: use PUT /runtime/deployments/{id}/credentials with a credential form published by GET /openapi.json
    • Dry-run: Skip the credentials step — the deployment runs in simulation mode (no real funds)
  3. Run the pre-deployment checklist
  4. Show the deployment confirmation summary and wait for explicit user confirmation
  5. PUT /runtime/deployments/{id}/status → {"action": "start"}
  6. Monitor: GET /runtime/deployments/{id}, GET /runtime/deployments/{id}/logs
  7. Stop: PUT /runtime/deployments/{id}/status → {"action": "stop"}

Pre-Deployment Checklist (MANDATORY)

Before PUT /runtime/deployments/{id}/status → {"action":"start"}:

For live deployments (credentials stored):

  1. Account ready — fetch GET /wallet and GET /context/venues. Proceed only when the returned wallet and Hyperliquid capability data show the required support; otherwise report the blocker.
  2. Credentials stored — inspect the credential state returned by GET /runtime/deployments/{id}. If credentials are required, attach the exact contract-defined payload with PUT /runtime/deployments/{id}/credentials.
  3. Identify wallets — GET /runtime/deployments/{id} → note wallet_address (agent wallet) and agent_wallet_address.
  4. Funds available — Check the managed wallet and live Hyperliquid state. Verify stake_amount × max_open_trades fits within available collateral with a fee buffer. If funding is insufficient and Unified API does not publish a venue deposit action, stop and tell the user what funding step remains unavailable.
  5. No existing positions/orders — Check clearinghouseState for open positions on the main wallet. If positions or orders exist, show the user details (pair, side, size, PnL) and ask them to close before deploying — leftover positions can block new entries or cause unexpected margin usage.

For dry-run deployments (no credentials): Skip steps 1–5, the deployment runs in simulation mode without real funds.

  1. Pair is tradeable — POST https://api.hyperliquid.xyz/info → {"type":"meta"} for standard perps, or {"type":"meta", "dex":"xyz"} (or the relevant dex name) for HIP3 pairs. Verify the coin name exists in the universe array.

Do NOT skip any step or assume it passed without the API call.

Getting Funds Back Out

Use POST /wallet/withdraw only with the request shape and verified destination published by the Unified contract. A typed POST /runtime/executions request may place or cancel supported orders; it is not an undocumented exit-all or sub-account transfer primitive. If the required unwind action is absent from GET /openapi.json, report it as unavailable. Every money-moving action requires an exact summary and explicit confirmation first.

Related skills

Strategy templates and primitives are separate skills in this library. Load one when the user's idea matches it, rather than writing a strategy from scratch.

Strategy templates: dca-weekly, grid-trading, funding-rate-arbitrage, funding-squeeze, basis-arb, breakout, mean-reversion, bollinger-reverter-4h, donchian-strong-regime, scalping

Primitives: regime-overlay (trend gate), dsl-exit-engine (ROI ladder + ratcheting trail), trade-thesis (pre-trade bull/bear case), backtesting (windows, sweeps, walk-forward), fees-optimizations (maker vs taker, fee budgeting)

Market scanning: intelligence — live multi-bucket scoring across Hyperliquid alts and HIP-3, deployed as multi-pair buckets

Other venues: aerodrome (Base spot AMM), lighter, polymarket

Funding an account: deposit-qr (payment QR for a Superior-managed wallet), external-deposit (bridging in from an external wallet)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hyperliquid AI skill do?

Use when backtesting, deploying, checking funding readiness, or debugging a Hyperliquid strategy through Superior Trade Unified API — writing Freqtrade configs and strategy code, running sweeps, checking managed-wallet balances, trading HIP-3 perps, or diagnosing a deployment that will not start or trade.

Why use Hyperliquid on TypingMind?

Because you install it once and use it with any model. Hyperliquid is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hyperliquid in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Superior-Trade/superior-skills/tree/main/skills/hyperliquid. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hyperliquid?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hyperliquid?

As many as you like. As long as a model supports skills, you can use Hyperliquid with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hyperliquid AI skill free?

Yes. It is published on GitHub by Superior-Trade under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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