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Ai Evaluation

Checked
sunnypatneedi·vlatest·other

Sunnypatneedi's ai-evaluation assesses AI outputs against defined criteria, providing scores and actionable feedback for improvement.

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 sunnypatneedi/claude-starter-kit --skill ai-evaluation -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

sunnypatneedi

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 sunnypatneedi/claude-starter-kit at bb46cf5d4f.

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

Commit
bb46cf5d4f
Manifest
skills/engineering/ai-evaluation/SKILL.md
Scanned
1 file, 451 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 ai-evaluation skill allows an AI agent to assess and rate the quality of generated text or code. It can provide feedback on aspects like helpfulness, accuracy, relevance, and safety. This skill is designed to help improve the output of other AI agents by providing structured evaluations.

When to use it

  • Evaluating draft content: Use this skill to get a quick assessment of blog posts, articles, or marketing copy before publishing.
  • Code review assistance: Have the agent evaluate code snippets for correctness, efficiency, and adherence to coding standards.
  • Improving chatbot responses: Assess chatbot replies to determine if they are helpful and address user needs effectively.
  • Safety checks on AI-generated content: Evaluate generated text for potentially harmful or biased statements.

Key capabilities

  • Text/Code Evaluation
  • Helpfulness Assessment
  • Accuracy Rating
  • Relevance Scoring
  • Safety Analysis

Example prompts

  • "Evaluate the following paragraph and provide a score for helpfulness: [paragraph of text]"
  • "Assess this Python code snippet for correctness and efficiency: [code snippet]"
  • "Rate this chatbot response on a scale of 1-5, considering accuracy and relevance to the user's query: [chatbot response]"

Tips & gotchas

The quality of the evaluation depends heavily on the clarity and specificity of your prompts. Providing context or specific criteria for evaluation will yield more useful results.