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Clig Eval Prompt

Checked
samzong·vlatest·ai-ml·MIT

Clig Eval Prompt assesses prompt quality and clarity, ensuring better AI responses by identifying potential issues and suggesting improvements.

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 samzong/samzong --skill clig-eval-prompt -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

samzong

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 samzong/samzong at c564f2a67e.

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

Commit
c564f2a67e
Manifest
.agents/skills/clig-eval-prompt/SKILL.md
Scanned
1 file, 83 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 clig-eval-prompt skill evaluates a given prompt and provides feedback on its quality. It assesses aspects like clarity, conciseness, potential biases, and overall effectiveness for achieving the desired outcome from an AI model. The skill aims to help users refine their prompts to improve the performance of AI agents.

When to use it

  • Prompt Optimization: Before deploying a prompt in a production environment, evaluate its likely impact on the AI agent's output.
  • Bias Detection: Identify potential biases or problematic phrasing within a prompt that could lead to unfair or undesirable results.
  • Training New Users: Help users learn how to write effective prompts by providing constructive feedback and guidance.
  • Troubleshooting Poor Performance: Analyze prompts used with an AI agent that is not performing as expected, identifying areas for improvement.

Key capabilities

  • Prompt evaluation
  • Bias detection
  • Clarity assessment
  • Conciseness analysis
  • Feedback generation

Example prompts

  • "Evaluate this prompt: 'Write a short story about a cat.'"
  • "Can you analyze this prompt for potential biases? 'Describe the typical CEO.'"
  • "Give me feedback on how to improve this prompt: 'Generate marketing copy for our new product.'"

Tips & gotchas

The quality of the evaluation depends heavily on the clarity and specificity of the prompt provided to clig-eval-prompt. It's best used with prompts intended for generative AI models.