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Agent Skill Linter

Listed
william-yeh·vlatest·agents·Apache-2.0

Analyzes agent code for potential errors, inefficiencies, and adherence to best practices, improving reliability.

Repository

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 william-yeh/agent-skill-linter --skill agent-skill-linter -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

william-yeh

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 2 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: agentskills.io, img.shields.io.

    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.

    Hosts contacted

    www.apache.orgstandardsgithub.comsource hostimg.shields.ioundeclaredagentskills.ioundeclared

    What it found

    • skill/scripts/fixers.py:179contacts img.shields.io
      [![License](https://img.shields.io/github/license/{owner}/{repo})](LICENSE)
    • skill/scripts/fixers.py:180contacts img.shields.io
      [![Agent Skills](https://img.shields.io/badge/Agent%20Skills-compatible-blue)]\
    • skill/scripts/fixers.py:181contacts agentskills.io
      (https://agentskills.io)

  • 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 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 william-yeh/agent-skill-linter at 3ab47f0bc7.

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

Commit
3ab47f0bc7
Manifest
skill/SKILL.md
Scanned
10 files, 2,890 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 agent-skill-linter skill analyzes agent skill descriptions to identify potential issues and improve their quality. It checks for things like missing information, unclear language, and inconsistencies in formatting. This helps ensure that skills are easily understandable and usable by other agents or developers.

When to use it

  • Skill Development: Use this skill when creating new agent skills to catch errors early on.
  • Skill Maintenance: Employ the linter during regular updates to existing skills, ensuring continued quality.
  • Team Collaboration: Integrate into a team workflow for peer review of agent skills before publication.
  • Registry Quality Control: Use it to maintain consistency and accuracy within an AI agent skill registry like TrustedSkills.

Key capabilities

  • Analyzes skill descriptions for clarity and completeness.
  • Identifies potential formatting inconsistencies.
  • Flags missing information or unclear language.
  • Provides suggestions for improvement.

Example prompts

  • "Lint this skill description: [paste skill description here]"
  • "Check the quality of this agent skill's documentation."
  • "Analyze this skill and suggest improvements to its clarity."

Tips & gotchas

The linter’s effectiveness depends on a well-defined set of rules. Ensure that the underlying ruleset is appropriate for your specific needs and standards for agent skills.