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Grimoire Hyperliquid

Checked
franalgaba·vlatest·other

Grimoire Hyperliquid generates creative text formats like poems and stories based on user prompts, boosting content creation speed & inspiration.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add franalgaba/grimoire --skill grimoire-hyperliquid -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

franalgaba

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned franalgaba/grimoire at 2cca3994a2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
1 file, 85 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The grimoire-hyperliquid skill provides tools and functionalities related to interacting with blockchain protocols, particularly focusing on HyperLiquid. It enables AI agents to perform actions such as querying data, executing trades, or managing assets on the HyperLiquid platform.

When to use it

  • When an AI agent needs to access real-time market data from HyperLiquid for trading decisions.
  • To automate trade execution based on predefined strategies on the HyperLiquid blockchain.
  • For monitoring and managing digital assets stored within the HyperLiquid ecosystem.

Key capabilities

  • Querying blockchain data from HyperLiquid
  • Executing trades or transactions via HyperLiquid API
  • Managing digital asset positions on HyperLiquid

Example prompts

  • "Fetch the latest price of ETH on HyperLiquid."
  • "Execute a trade to buy 1 BTC at market price on HyperLiquid."
  • "Show my current portfolio holdings on HyperLiquid."

Tips & gotchas

  • Ensure that your AI agent has access to the necessary API keys and permissions for interacting with HyperLiquid.
  • Be aware of potential latency or rate limits when making frequent requests to the HyperLiquid API.