Skill Introduction

Overview

Hyperliquid market data, account history, trade review.

Core value

Turns reusable Testing know-how into an installable skill, helping users complete github, community, ai, ai-agent work faster.

Target users

Developers, testers, and maintainers who handle Testing tasks in Focus Code.
Teams that already trust workflows or content from NousResearch.
Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

Read the skill content first to confirm required inputs, expected outputs, and dependencies.
Try it on a small task before relying on it for critical work.
Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

Tasks related to github, community, ai, ai-agent that need a reusable execution flow.
Converting a community repo, team convention, or personal workflow into day-to-day assistance.
Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

Results depend on the quality of the original skill content and may need human correction.
It does not replace code review, tests, security review, or professional judgment.
External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

Structured around Testing, making it easier to discover and reuse than loose prompt snippets.
Marked as GitHub, which helps users judge trust and maintenance expectations.
Keeps the original source link available for repository, documentation, or discussion follow-up.
Tagged with github, community, ai, ai-agent, so it can be filtered by concrete task intent.

Install and use

Install

Copy Install Command

focus install hyperliquid-2be730

View source

Detail Preview

SKILL.md

Primary filemarkdown7 KB

name: hyperliquid description: Hyperliquid market data, account history, trade review. version: 0.1.0 author: Hugo Sequier (Hugo-SEQUIER), Hermes Agent license: MIT platforms: [linux, macos, windows] metadata: hermes: 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).

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/.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: ~/.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/.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

--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 ~/.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 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.

Verification

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

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

hyperliquid