hyperliquid

name	hyperliquid
description	Hyperliquid market data, account history, trade review.
version	0.1.0
author	Hugo Sequier (Hugo-SEQUIER), Fabric
license	MIT
platforms	["linux","macos","windows"]
metadata	{"fabric":{"tags":["Hyperliquid","Blockchain","Crypto","Trading","Perpetuals","Spot","DeFi"],"related_skills":[]}}

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 ${FABRIC_HOME:-~/.fabric}/.env for two optional defaults:

• HYPERLIQUID_API_URL — defaults to https://api.hyperliquid.xyz. Set to https://api.hyperliquid-testnet.xyz 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: ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py

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How to Run

Invoke through the terminal tool:

python3 ~/.fabric/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 ${FABRIC_HOME:-~/.fabric}/.env.

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Procedure

1. Discover DEXs and Markets

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py dexs

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  markets --limit 15 --sort volume

python3 ~/.fabric/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

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  candles BTC --interval 1h --hours 72 --limit 48

python3 ~/.fabric/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 ~/.fabric/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 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  state 0xabc...

python3 ~/.fabric/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 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  fills 0xabc... --hours 72 --limit 25

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  orders --limit 25

6. Generate a Trade Review

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  review 0xabc... --hours 72 --fills 50

python3 ~/.fabric/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 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  export BTC --interval 1h --hours 168 --output ./btc-1h-7d.json

python3 ~/.fabric/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

python3 ~/.fabric/skills/blockchain/hyperliquid/scripts/hyperliquid_client.py \
  markets --limit 5

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