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Advanced Evaluation

Checked
chakshugautam·vlatest·other

This skill deeply analyzes text for nuanced sentiment, bias, and factual accuracy, boosting reliable insights & decision-making.

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 chakshugautam/games --skill advanced-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

chakshugautam

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 chakshugautam/games at 0108212484.

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

Commit
0108212484
Manifest
.claude/skills/advanced-evaluation/SKILL.md
Scanned
5 files, 1,604 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, chakshugautam-advanced-evaluation, provides a mechanism to evaluate and refine AI agent performance. It allows users to assess an agent's output against specific criteria and provide feedback, ultimately improving its capabilities. The tool is designed for iterative improvement of AI agents through structured evaluation processes.

When to use it

  • Debugging Agent Behavior: Identify why an agent isn’t performing as expected in a particular scenario.
  • Refining Task Completion: Improve the quality and accuracy of an agent's output on complex tasks.
  • Evaluating Different Approaches: Compare the effectiveness of various prompting strategies or agent configurations.
  • Measuring Progress Over Time: Track improvements to an AI agent’s performance after training or adjustments.

Key capabilities

  • Evaluation against specific criteria
  • Feedback provision for iterative improvement
  • Assessment of agent output quality and accuracy
  • Comparison of different approaches

Example prompts

  • "Evaluate the agent's response to this prompt: [prompt text] using these criteria: [criteria list]"
  • "Provide feedback on the agent’s performance in completing this task: [task description]."
  • "Compare the outputs of two agents given the same input and rate them based on [metric]."

Tips & gotchas

The effectiveness of this skill depends heavily on providing clear and well-defined evaluation criteria. Vague or subjective criteria will lead to less actionable feedback for the AI agent.