# Judge

Launch a meta-judge then a judge sub-agent to evaluate results produced in the current...

- Repository: https://github.com/NeoLabHQ/context-engineering-kit (1797 stars)
- Category: AI and agents
- License: GPL-3.0
- Last updated: 2026-08-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NeoLabHQ/context-engineering-kit --skill judge -g -a claude-code -y`
Codex: `npx skills add NeoLabHQ/context-engineering-kit --skill judge -g -a codex -y`
Cursor: `npx skills add NeoLabHQ/context-engineering-kit --skill judge -g -a cursor -y`
Gemini CLI: `npx skills add NeoLabHQ/context-engineering-kit --skill judge -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NeoLabHQ/context-engineering-kit`

## Description

Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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**:

The rest: https://github.com/NeoLabHQ/context-engineering-kit/blob/HEAD/antigravity/skills/judge/SKILL.md