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hyperliquid Skill

AI Agent SkillPythonOpen source

Hyperliquid market data, account history, trade review. Published by NousResearch in hermes-agent.

Decision snapshot

Is this a fit?

Best for

Data analysis, Includes SKILL.md, Reusable instructions

Works with

Compatibility not yet detected.

Access

No auth authentication

Setup

Copy skill directory

Project health

14 days ago · MIT license

Considerations

Access note: No auth.

What is hyperliquid Skill?

Hyperliquid market data, account history, trade review. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
100/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Declared skill metadata

  • Declared author: Hugo Sequier (Hugo-SEQUIER), Hermes Agent
  • Declared license: MIT
  • Source file: optional-skills/blockchain/hyperliquid/SKILL.md

These fields retain source and confidence evidence from the indexed SKILL.md.

Compatibility and setup

Copy skill directory
  • Install or run with Copy skill directory
  • No auth

Requirements and access

No auth

Security and permissions

Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.

No auth authentication

When to use hyperliquid Skill

  • Use it for data analysis.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: NousResearch
  • Repository: NousResearch/hermes-agent
  • Skill file: optional-skills/blockchain/hyperliquid/SKILL.md

What it does

Hyperliquid market data, account history, trade review.

Skill instructions

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 ${HERMESHOME:-~/.hermes}/.env for two optional defaults: - HYPERLIQUIDAPIURL — defaults to https://api.hyperliquid.xyz. Set to https://api.hyperliquid-testnet.xyz for testnet. - HYPERLIQUIDUSERADDRESS — default a

Verified compatibility and discovery

Frequently asked questions

What is hyperliquid?

hyperliquid is a open-source AI agent skill with Copy skill directory. Hyperliquid market data, account history, trade review.

Who is hyperliquid best for?

hyperliquid is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install hyperliquid?

Install or run hyperliquid using Copy skill directory. Check hyperliquid for the latest setup command.

Is hyperliquid actively maintained?

hyperliquid may need a closer maintenance check before production use.

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Stars
236,516
Forks
47,768
Last commit
14 days ago
Last verified
Aug 26, 2026
Metadata fetched
Aug 26, 2026
Repository age
1 year
License
MIT

Project health auto-fetched from the source repository.

Maintain this resource?

Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.

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