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Agent Evaluation

Test and compare agent behavior with versioned cases, explicit verifiers and honest uncertainty reporting.

Source Download skill
Repository
sickn33/agentic-awesome-skills
Stars
49,023
Licence
MIT
Files
2 files

What it does

Once installed, the agent follows a disciplined procedure when asked to check whether a changed agent, prompt or tool setup works better or worse than before. It freezes test cases and pass criteria before running anything, separates real failures from harness bugs and outages, keeps every attempt on record, and avoids claiming reliability from too few runs. It also includes a small helper for computing a Wilson confidence interval on pass rates.

Great for

  • Engineers comparing a baseline agent against a candidate after a prompt, model or tool change
  • Teams reproducing an observed agent failure and building a regression suite
  • Anyone who needs an honest statement of uncertainty rather than a single headline success rate

Skip it if

  • Quick one-off checks of a chatbot answer, where this procedure is heavier than needed
  • Teams without a versioned case set or access to isolated test targets, since the skill assumes these exist
  • Use on real customer data or production credentials, which the skill itself says to avoid

Try asking

  • “Compare my candidate prompt against the baseline on this set of 30 synthetic cases and report regressions”
  • “Reproduce this agent failure and classify whether it is agent behaviour, verifier ambiguity or an outage”
  • “Calculate a 95% Wilson interval for 47 passes out of 50 runs of one case”
  • “Design a regression pipeline for my tool-calling agent with critical permission checks”
Step-by-step guide: how to use Agent EvaluationInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 2 original files, the MIT licence and an attribution note.

    agent-evaluation.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip agent-evaluation.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip agent-evaluation.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Freeze the case IDs, repeat counts and pass criteria before running, and keep old results when criteria change
  • Use synthetic or redacted inputs and isolated targets; never point the harness at production systems
  • Treat repeated runs of the same case as correlated, and use case-level uncertainty rather than pooling them as independent samples

What's inside

  • references/architecture-sketches.md
  • SKILL.md

Redistributed unmodified from sickn33/agentic-awesome-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.