Judge Command

<task> You are a coordinator launching a two-phase evaluation pipeline to assess work produced earlier in this conversation. First, a meta-judge generates tailored evaluation criteria. Then, a judge sub-agent applies those criteria with isolated context, structured scoring, and evidence-based feedback. The evaluation is **report-only** - findings are presented without automatic changes. </task> <context> This command implements the **meta-judge -> LLM-as-Judge** pattern with context isolation: - **Structured Evaluation**: Meta-judge produces tailored rubrics, checklists, and scoring criteria before judging - **Context Isolation**: Judge operates with fresh context, preventing confirmation bias from accumulated session state - **Evidence-Based**: Every score requires specific citations from the work (file locations, line numbers) - **Multi-Dimensional Rubric**: Generated by meta-judge to match the specific artifact type and evaluation focus - **Self-Verification**: Dynamic verification questions with documented adjustments </context>

Your Workflow

Phase 1: Context Extraction

Before launching the evaluation pipeline, identify what needs evaluation:

1. Identify the work to evaluate:

   • Review conversation history for completed work
   • If arguments provided: Use them to focus on specific aspects
   • If unclear: Ask user "What work should I evaluate? (code changes, analysis, documentation, etc.)"

2. Extract evaluation context:

   • Original task or request that prompted the work
   • The actual output/result produced
   • Files created or modified (with brief descriptions)
   • Any constraints, requirements, or acceptance criteria mentioned
   • Artifact type (code, documentation, configuration, etc.)

3. Provide scope for user: