eval
Evaluate and rank agent results by metric or LLM judge for an AgentHub session.
npx skills add majiayu000/claude-skill-registry --skill eval-alirezarezvani-claude-skills --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.
# /hub:eval — Evaluate Agent Results Rank all agent results for a session. Supports metric-based evaluation (run a command), LLM judge (compare diffs), or hybrid. ## Usage ``` /hub:eval # Eval latest session using configured criteria /hub:eval 20260317-143022 # Eval specific session /hub:eval --judge # Force LLM judge mode (ignore metric config) ``` ## What It Does ### Metric Mode (eval command configured) Run the evaluation command in each agent's worktree: ```bash python {skill_path}/scripts/result_ranker.py \ --session {session-id} \ --eval-cmd "{eval_cmd}" \ --metric {metric} --direction {direction} ``` Output: ``` RANK AGENT METRIC DELTA FILES 1 agent-2 142ms -38ms 2 2 agent-1 165ms -15ms 3 3 agent-3 190ms +10ms 1 Winner: agent-2 (142ms) ``` ### LLM Judge Mode (no eval command, or --judge flag) For each agent: 1. Get the diff: `git diff {base_branch}...{agent_branch}` 2. Read the agent's result post from `.agenthub/board/results/agent-{i}-result.md` 3. Compare all diffs and rank by: - **Correctness** — Does it solve the task? - **Simplicity** — Fewer lines changed is better (when equal correctness) - **Quality** — Clean execution, good structure, no regressions Present ranking
- Usage
- What It Does
- Metric Mode (eval command configured)
- LLM Judge Mode (no eval command, or --judge flag)
- Hybrid Mode
- After Eval
python {skill_path}/scripts/result_ranker.py \
python {skill_path}/scripts/session_manager.py --update {session-id} --state evaluatingWhat does the eval skill do?
Evaluate and rank agent results by metric or LLM judge for an AgentHub session.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill eval-alirezarezvani-claude-skills --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 majiayu000/claude-skill-registry, a repository with 534 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.