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Evaluating Skills With Models

Checked
taisukeoe·vlatest·agents·Apache-2.0

This skill assesses user-provided content using language models to determine quality and suitability – a valuable tool for verification & refinement.

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 taisukeoe/agentic-ai-skills-creator --skill evaluating-skills-with-models -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

taisukeoe

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 taisukeoe/agentic-ai-skills-creator at fe7929b098.

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

Commit
fe7929b098
Manifest
plugins/skills-helper/skills/evaluating-skills-with-models/SKILL.md
Scanned
3 files, 703 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

This skill allows AI agents to evaluate other skills using language models. It can assess the quality, relevance, and potential usefulness of a given skill based on its description and example prompts. The evaluation is performed by leveraging large language models to provide structured feedback and ratings.

When to use it

  • Skill Selection: Help an agent choose the best skill from a list of options for a specific task.
  • Quality Assurance: Automatically assess newly created or updated skills before they are deployed.
  • Skill Improvement: Identify areas where existing skills can be improved based on model feedback.
  • Skill Discovery: Quickly determine if a skill is likely to meet your needs without extensive manual testing.

Key capabilities

  • Language Model Integration: Uses language models for evaluation.
  • Automated Assessment: Provides automated ratings and feedback.
  • Structured Feedback: Delivers evaluations in a structured format.
  • Skill Quality Analysis: Analyzes skills based on description and prompts.

Example prompts

  • "Evaluate the 'summarization-skill' skill, providing a rating and explaining your reasoning."
  • "Assess this skill description: '[Skill Description]' and suggest improvements to its clarity."
  • "Can you determine if this skill is relevant for generating marketing copy?"

Tips & gotchas

The quality of the evaluation depends heavily on the capabilities of the underlying language model. Ensure the selected language model has sufficient understanding of the domain being evaluated.