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.