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/hub:eval — Evaluate Agent Results

Engineering - POWERFUL eval Source

Install: claude /plugin install engineering-advanced-skills

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:

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 rankings with justification.

Example LLM judge output for a content task:

RANK  AGENT    VERDICT                               WORD COUNT
1     agent-1  Strong narrative, clear CTA            1480
2     agent-3  Good data points, weak intro           1520
3     agent-2  Generic tone, no differentiation       1350

Winner: agent-1 (strongest narrative arc and call-to-action)

Hybrid Mode

  1. Run metric evaluation first
  2. If top agents are within 10% of each other, use LLM judge to break ties
  3. Present both metric and qualitative rankings

After Eval

  1. Update session state:

    python {skill_path}/scripts/session_manager.py --update {session-id} --state evaluating
    

  2. Tell the user:

  3. Ranked results with winner highlighted
  4. Next step: /hub:merge to merge the winner
  5. Or /hub:merge {session-id} --agent {winner} to be explicit