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Agent Evaluation

Checked
glennguilloux·vlatest·agents·GPL-3.0

Evaluates agent performance across diverse tasks using a robust scoring system and detailed qualitative feedback.

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 glennguilloux/context-engineering-kit --skill agent-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

glennguilloux

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 glennguilloux/context-engineering-kit at 245278227a.

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

Commit
245278227a
Manifest
skills/agent-evaluation/SKILL.md
Scanned
2 files, 3,221 lines
Copies in repo
2 — all of them scanned
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 glennguilloux-agent-evaluation skill provides a framework for evaluating the performance of AI agents. It allows users to define evaluation criteria and assess an agent's responses against those criteria, providing structured feedback. This facilitates iterative improvement and ensures alignment with desired outcomes.

When to use it

  • Testing new agent versions: Evaluate changes in agent behavior after updates or modifications.
  • Comparing different agents: Objectively compare the performance of multiple AI agents on a specific task.
  • Identifying areas for agent improvement: Pinpoint weaknesses in an agent's responses through structured assessment.
  • Ensuring alignment with guidelines: Verify that an agent consistently adheres to defined rules or principles.

Key capabilities

  • Definable evaluation criteria
  • Structured response assessment
  • Performance tracking over time
  • Feedback generation for iterative improvement

Example prompts

  • "Evaluate the following agent response: '[Agent Response]' against these criteria: [Criteria List]"
  • "Compare the performance of Agent A and Agent B on this task: [Task Description] using the evaluation framework."
  • "Assess this agent's response to 'User Query': '[User Query]' and provide feedback for improvement."

Tips & gotchas

The effectiveness of this skill relies on clearly defined and measurable evaluation criteria. Vague or subjective criteria will lead to inconsistent results.