Hyperliquid

Hyperliquid market data, account history, trade review.

Skill metadata

Source	Optional — install with hermes skills install official/blockchain/hyperliquid
Path	optional-skills/blockchain\hyperliquid
Version	0.1.0
Author	Hugo Sequier (Hugo-SEQUIER), Hermes Agent
License	MIT
Platforms	linux, macos, windows
Tags	Hyperliquid, Blockchain, Crypto, Trading, Perpetuals, Spot, DeFi

Reference: full SKILL.md

INFO

The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.

Hyperliquid 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).

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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

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Prerequisites

Stdlib only — no external packages, no API key.

The script reads ${HERMES_HOME:-~/.hermes}/.env for two optional defaults:

• HYPERLIQUID_API_URL — defaults to Set to for testnet.
• HYPERLIQUID_USER_ADDRESS — default address for state, spot-balances, fills, orders, and review. 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

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How to Run

Invoke through the terminal tool:

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py <command> [args]

Add --json to any command for machine-readable output.

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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.

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Procedure

1. Discover DEXs and Markets

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py dexs

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  markets --limit 15 --sort volume

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  spots --limit 15

• --dex only applies to perp endpoints; omit for the first perp dex.
• Spot pairs may show as PURR/USDC or aliases like @107.
• HIP-3 markets prefix the coin with the dex, e.g. mydex:BTC.

2. Pull Historical Market Data

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  candles BTC --interval 1h --hours 72 --limit 48

python ~/.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

python ~/.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

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  state 0xabc...

python ~/.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

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  fills 0xabc... --hours 72 --limit 25

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  orders --limit 25

6. Generate a Trade Review

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  review 0xabc... --hours 72 --fills 50

python ~/.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

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  export BTC --interval 1h --hours 168 --output ./btc-1h-7d.json

python ~/.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.

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Pitfalls

• Public info endpoints are rate-limited. Large historical queries may return capped windows; iterate with later startTime values.
• fills --hours ... uses userFillsByTime, which only exposes a recent rolling window — not full archive history.
• historicalOrders returns recent orders only; not a full export.
• The review command is heuristic. It cannot reconstruct intent, order placement quality, or true slippage from fills alone.
• The export command writes a normalized dataset, not a backtest engine. You still need your own slippage/fill model.
• Spot aliases like @107 are valid identifiers even when the UI shows a friendlier name.
• l2 is a point-in-time snapshot, not a time series.

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Verification

python ~/.hermes/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  markets --limit 5

Should print the top Hyperliquid perp markets by 24h notional volume.