judge

Evaluates task commits against specifications using dual logic and consistency checks.

Updated Feb 6, 2026
One-click install
npx skills add https://github.com/dcarmitage/claws --skill judge-dcarmitage
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: judge
Source: https://github.com/dcarmitage/claws/tree/main/skills/dual-judge
Command: npx skills add https://github.com/dcarmitage/claws --skill judge-dcarmitage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Run dual-judge evaluation (logic + consistency) on a task's commit to verify whether the output meets the specification. This is triggered automatically after a task is marked done, or can be invoked manually with /judge.

Core Features & Use Cases

  • Logic & Consistency Judging: Run parallel LLMS-based checks to assess the quality and alignment with specs.
  • Automated QA Workflow: Integrates into task pipelines to provide quick verdicts on code and task outputs.
  • Use Case: After completing a task, apply the judge to ensure the submission satisfies the spec before progressing.

Quick Start

Use the judge skill to evaluate the latest commit against its spec via /judge.

Frequently Asked Questions about judge

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate code review to validate a task commit against its specification?▼

Automate code review by running dual-judge evaluation on a task commit to verify logic and consistency against the specification. This QA workflow checks if outputs meet design requirements before progressing.

What is dual-judge evaluation for quality assurance in software engineering?▼

Dual-judge evaluation is a QA process that runs parallel LLM-based logic and consistency checks on a commit. It assesses code quality and alignment with specifications to generate a pass or fail verdict.

When do I need to run a consistency and logic judge on my repository commits?▼

Run a consistency and logic judge after marking a task done to ensure the submission satisfies the spec. It can be triggered automatically in task pipelines or invoked manually to validate outputs.

Can I use LLM-based quality assurance without setting up external dependencies?▼

Yes, you can run LLM-based quality assurance without external dependencies. The judge skill operates standalone using internal logic_judge and consistency_judge scripts to evaluate repository commits.

How do I evaluate the latest commit against a spec using a manual command?▼

Evaluate the latest commit by invoking the manual /judge command. This triggers the dual-judge evaluation to validate the commit against an optional spec path and taskboard context.

What limitations exist when using automated LLM judges for task completion validation?▼

Automated LLM judges require access to the repository commit, optional spec path, and taskboard context to generate a verdict. Without these inputs, the logic and consistency checks cannot evaluate alignment.