
Hyperliquid
FreeAccess real-time and historical Hyperliquid market data.
Free · Opens the source repo
What Hyperliquid does
The Hyperliquid skill provides developers and traders with a straightforward way to query market and account data from the Hyperliquid trading platform. Utilizing the public /info endpoint, this skill allows for read-only access to various market metrics without the need for an API key or signing, making it easy to integrate into existing workflows. Users can execute a range of commands to retrieve specific data, including market conditions, account balances, and trade history.
With 12 available commands, users can explore decentralized exchanges (DEXs), view market data, and analyze trading performance. For instance, commands like dexs, markets, and candles allow users to gather information on available trading pairs and historical price movements. The skill also supports reviewing account activity through commands such as fills, orders, and review, which provide insights into recent trades and overall performance metrics.
This skill is particularly beneficial for developers building trading applications or for traders looking to analyze their market positions and trading strategies. By leveraging the Hyperliquid skill, users can gain valuable insights into market trends, assess their trading performance, and prepare data for backtesting strategies. The output can be formatted in JSON for easy consumption by other applications or systems, enhancing its utility in automated trading setups.
Overall, the Hyperliquid skill is a powerful tool for anyone involved in trading on the Hyperliquid platform, providing essential data access in a simple and efficient manner.
When to use it
Use this skill when you need to retrieve market data or account information from Hyperliquid, especially for analysis or reporting purposes.
When not to use it
This skill is not suitable for trading execution or for accessing private account information beyond what is available through public endpoints.
What you can build with it
Market Analysis
Use the skill to query current market conditions and historical price data for informed trading decisions.
Account Performance Review
Retrieve and analyze your trading history and account balances to assess performance over time.
Data Export for Backtesting
Export market data in JSON format for use in backtesting trading strategies or analysis.
How to install Hyperliquid
View source1. Install with the skills CLI
npx skills add nousresearch/hermes-agent/hyperliquid --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by nousresearchHyperliquid Skill
Query Hyperliquid market and account data through the public /info endpoint.
Read-only — no API key, no signing, no order placement.
12 commands: dexs, markets, spots, candles, funding, l2, state,
spot-balances, fills, orders, review, export. Stdlib only
(urllib, json, argparse).
When to Use
- User asks for Hyperliquid perp or spot market data, candles, funding, or L2 book
- User wants to inspect a wallet's perp positions, spot balances, fills, or orders
- User wants a post-trade review combining recent fills with market context
- User wants to inspect builder-deployed perp dexs or HIP-3 markets
- User wants a normalized JSON export of candles + funding for backtesting prep
Prerequisites
Stdlib only — no external packages, no API key.
The script reads ${HERMES_HOME:-~/.hermes}/.env for two optional defaults:
HYPERLIQUID_API_URL— defaults tohttps://api.hyperliquid.xyz. Set tohttps://api.hyperliquid-testnet.xyzfor testnet.HYPERLIQUID_USER_ADDRESS— default address forstate,spot-balances,fills,orders, andreview. If unset, pass the address as the first positional argument.
A project .env in the current working directory is honored as a dev fallback.
Helper script: ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py
How to Run
Invoke through the terminal tool:
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py <command> [args]
Add --json to any command for machine-readable output.
Quick Reference
hyperliquid_client.py dexs
hyperliquid_client.py markets [--dex DEX] [--limit N] [--sort volume|oi|funding_abs|change_abs|name]
hyperliquid_client.py spots [--limit N]
hyperliquid_client.py candles <coin> [--interval 1h] [--hours 24] [--limit N]
hyperliquid_client.py funding <coin> [--hours 72] [--limit N]
hyperliquid_client.py l2 <coin> [--levels N]
hyperliquid_client.py state [address] [--dex DEX]
hyperliquid_client.py spot-balances [address] [--limit N]
hyperliquid_client.py fills [address] [--hours N] [--limit N] [--aggregate-by-time]
hyperliquid_client.py orders [address] [--limit N]
hyperliquid_client.py review [address] [--coin COIN] [--hours N] [--fills N]
hyperliquid_client.py export <coin> [--interval 1h] [--hours N] [--output PATH]
For state, spot-balances, fills, orders, and review, the address is
optional when HYPERLIQUID_USER_ADDRESS is set in ${HERMES_HOME:-~/.hermes}/.env.
Procedure
1. Discover DEXs and Markets
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py dexs
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
markets --limit 15 --sort volume
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
spots --limit 15
--dexonly applies to perp endpoints; omit for the first perp dex.- Spot pairs may show as
PURR/USDCor aliases like@107. - HIP-3 markets prefix the coin with the dex, e.g.
mydex:BTC.
2. Pull Historical Market Data
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
candles BTC --interval 1h --hours 72 --limit 48
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
funding BTC --hours 168 --limit 30
Time-range endpoints paginate. For larger windows, repeat with a later
startTime or use export (below).
3. Inspect Live Order Book
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
l2 BTC --levels 10
Use when asked about book depth, near-term liquidity, or potential market impact of a large order.
4. Review an Account
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
state 0xabc...
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
spot-balances
state returns perp positions; spot-balances returns spot inventory.
Use these for "how are my positions?", "what am I holding?", "how much is
withdrawable?".
5. Review Fills and Orders
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
fills 0xabc... --hours 72 --limit 25
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
orders --limit 25
6. Generate a Trade Review
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
review 0xabc... --hours 72 --fills 50
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
review --coin BTC --hours 168
Reports realized PnL, fees, win/loss counts, coin breakdowns, market trend and average funding for each traded perp, plus heuristics (fee drag, concentration, counter-trend losses).
For deeper post-trade analysis: start with review to find problem coins
or windows → pull fills and orders for that period → pull candles
and funding for each traded coin → judge decision quality separately
from outcome quality.
7. Export a Reusable Dataset
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
export BTC --interval 1h --hours 168 --output ./btc-1h-7d.json
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
export BTC --interval 15m --hours 72 --end-time-ms 1760000000000
Output JSON contains: schema version, source metadata, exact time window,
normalized candle rows, normalized funding rows, summary stats. Use
--end-time-ms for reproducible windows.
Pitfalls
- Public info endpoints are rate-limited. Large historical queries may
return capped windows; iterate with later
startTimevalues. fills --hours ...usesuserFillsByTime, which only exposes a recent rolling window — not full archive history.historicalOrdersreturns recent orders only; not a full export.- The
reviewcommand is heuristic. It cannot reconstruct intent, order placement quality, or true slippage from fills alone. - The
exportcommand writes a normalized dataset, not a backtest engine. You still need your own slippage/fill model. - Spot aliases like
@107are valid identifiers even when the UI shows a friendlier name. l2is a point-in-time snapshot, not a time series.
Verification
python3 ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
markets --limit 5
Should print the top Hyperliquid perp markets by 24h notional volume.
Frequently asked questions about Hyperliquid
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