testing-skills-with-subagents

Apply RED-GREEN-REFACTOR cycles to develop AI skills with measurable pass/fail criteria.

3|Updated Oct 18, 2025
One-click install
npx skills add https://github.com/DYAI2025/Stoppclock-page --skill testing-skills-with-subagents-dyai2025
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: testing-skills-with-subagents
Source: https://github.com/DYAI2025/Stoppclock-page/tree/main/stoppclock_speckit/.claude/commands/SKILL (18).md
Command: npx skills add https://github.com/DYAI2025/Stoppclock-page --skill testing-skills-with-subagents-dyai2025

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill ensures that AI skills are robust and effective by applying Test-Driven Development (TDD) principles to their creation. It helps identify and eliminate loopholes that agents might exploit to bypass rules, especially under pressure.

Core Features & Use Cases

  • RED Phase (Baseline Testing): Run scenarios without the skill to observe and document agent failures and rationalizations.
  • GREEN Phase (Skill Writing): Craft the skill to address observed failures, ensuring agent compliance.
  • REFACTOR Phase (Loophole Closing): Refine the skill to counter new rationalizations, making it bulletproof.
  • Use Case: Develop new AI skills for critical workflows, guaranteeing they are followed consistently and reliably by all agents, even in high-stakes situations.

Quick Start

1. RED: Create a pressure scenario. Run WITHOUT your skill.

Document agent's exact rationalizations.

2. GREEN: Write your skill to prevent those specific failures.

Run WITH skill; agent should comply.

3. REFACTOR: If agent finds new excuses, add explicit counters.

Re-test until bulletproof.

Frequently Asked Questions about testing-skills-with-subagents

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

FAQPage Schema
How do I test AI skills to ensure agents follow them consistently?

Test-Driven Development (TDD) for skills uses a RED-GREEN-REFACTOR cycle: run scenarios without the skill to document agent failures, write the skill to address those failures, then refine it to counter new rationalizations. This approach exposes loopholes agents might exploit and makes skills bulletproof.

What's the best way to close loopholes in AI agent behavior?

Use subagent testing to run pressure scenarios and capture the exact rationalizations agents use to bypass rules. Document each failure, craft a skill to prevent it, then re-test with variations. Iterate until the agent complies even under high-stakes pressure.

How do I validate a new skill before deploying it to production?

Establish a baseline by running your scenario without the skill and logging failures. Apply the skill and verify compliance. Then stress-test with pressure cases and refined rationalizations. Use measurable pass/fail criteria to confirm the skill blocks all documented workarounds.

Can I use TDD principles to develop AI skills for critical workflows?

Yes. TDD-style subagent testing applies RED-GREEN-REFACTOR cycles to skill development, ensuring agents follow rules consistently in high-stakes situations. It guarantees compliance by systematically identifying and eliminating behavioral loopholes before deployment.

What do I need to start testing skills with subagents?

You need a baseline scenario, scripted pressure cases designed to trigger agent rationalizations, rationalization logging to capture exact workarounds, and measurable pass/fail criteria. Start with the RED phase—run without the skill to document what agents do wrong.

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