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Prompt Evaluator

Checked
sunhao25·vlatest·ai-ml

This tool assesses prompts for clarity, effectiveness, and potential issues, helping users craft better instructions for AI models.

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 sunhao25/prompt-evaluator-skill --skill prompt-evaluator -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

sunhao25

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 sunhao25/prompt-evaluator-skill at 2d5dd4fd16.

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

Commit
2d5dd4fd16
Manifest
prompt-evaluator-skill-repo/skills/prompt-evaluator/SKILL.md
Scanned
5 files, 1,858 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 prompt evaluator skill assesses the quality of generated text based on provided criteria. It can analyze responses for helpfulness, relevance, and accuracy against a given prompt and evaluation rubric. The tool provides scores and justifications to help understand why a response received a particular rating.

When to use it

  • Evaluating chatbot performance: Determine how well a chatbot answers specific user queries based on predefined metrics.
  • Improving prompt engineering: Test different prompts to see which ones elicit the best responses from an AI model.
  • Assessing content generation quality: Evaluate the accuracy and relevance of generated articles, summaries, or creative writing pieces.
  • Benchmarking models: Compare the performance of different language models on a consistent set of prompts and evaluation criteria.

Key capabilities

  • Evaluates text responses based on provided rubrics.
  • Provides scores for helpfulness, relevance, and accuracy.
  • Offers justifications for assigned ratings.

Example prompts

  • "Evaluate the following response: '[response text]' against this rubric: [rubric details]"
  • "Score this chatbot answer: '[answer text]' based on its helpfulness and accuracy."
  • "Assess the relevance of this generated article: '[article text]' to the prompt: 'Summarize the history of AI.'"

Tips & gotchas

The quality of the evaluation depends heavily on a well-defined rubric. Ensure your rubrics are clear, specific, and measurable for best results.