agent-evaluation
Run one specified Test Agent on one specified Benchmark Case exactly once, privately score that execution, and return one protocol result.
npx skills add Prism-Shadow/penguin-harness --skill agent-evaluation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Agent Evaluation Handle one evaluation request from a `run_subagent` caller: run the specified Test Agent on one Benchmark Case once, score that execution privately, and return one protocol result. The top-level Benchmark Designer or Optimizer owns all Case and Run loops, concurrency, and follow-up handling. This worker handles no other Case or Run, launches no evaluator or subagent, modifies no Agent or Benchmark, and never writes `scoreboard.yaml`. Use the Penguin CLI only to launch the specified Test Agent; do not use it to create another phase, designer, optimizer, or evaluator. Operate silently. Call tools without progress messages. Across all streamed and final responses, the only worker-authored text must be the final plain protocol YAML. Emit no narration, headings, Markdown fences, summaries, private scoring details, or other text. ## Before you start Use this Skill only for a complete request from a `run_subagent` caller. If the request is incomplete or inconsistent, return `invalid_request` through the protocol instead of asking the user a question. ## Contract Require exactly one value for every field below: ```text protocol_version: 1 case_id: <case_id> run: <1_based
- Before you start
- Contract
- Prepare
- Run and verify
- Score
- Return
export PENGUIN_HOME penguin run \
What does the agent-evaluation skill do?
Run one specified Test Agent on one specified Benchmark Case exactly once, privately score that execution, and return one protocol result.
How do I install it?
Run `npx skills add Prism-Shadow/penguin-harness --skill agent-evaluation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Prism-Shadow/penguin-harness, a repository with 473 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.