Skip to content
TrustedSkillsbeta
Back to all skills

Eval Harness

Checked
peopleforrester·vlatest·ai-ml·MIT

Eval Harness allows you to systematically test and evaluate AI models’ performance across diverse datasets for robust results and reliable insights.

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 peopleforrester/claude-dotfiles --skill eval-harness -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

peopleforrester

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 peopleforrester/claude-dotfiles at db7caa0374.

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

Commit
db7caa0374
Manifest
skills/optimization/eval-harness/SKILL.md
Scanned
1 file, 103 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 peopleforrester-eval-harness skill provides a framework for evaluating AI agent responses against predefined criteria. It allows users to define evaluation metrics and compare different agent outputs, facilitating iterative improvement of agent performance. This harness is designed specifically for use with Claude agents.

When to use it

  • Benchmarking Agent Performance: Compare the output quality of different prompts or agent configurations on a consistent dataset.
  • Evaluating New Prompt Strategies: Quickly assess the impact of prompt engineering changes on response accuracy and relevance.
  • Identifying Areas for Improvement: Pinpoint specific areas where an AI agent struggles based on defined evaluation metrics.
  • Automated Testing: Integrate into automated workflows to continuously monitor agent performance over time.

Key capabilities

  • Claude Agent Specific
  • Evaluation Framework
  • Response Comparison

Example prompts

  • "Evaluate the following two responses from Claude using these criteria: [criteria list]."
  • "Compare the quality of these two prompts for summarizing a document, based on accuracy and conciseness."
  • "Run an evaluation harness with the prompt '...' and the dataset located at '...'"

Tips & gotchas

The skill is designed specifically for Claude agents; using it with other models may produce unexpected results. You will need to provide clear and specific evaluation criteria for accurate assessments.