testing-skills-with-subagents

Run RED-GREEN-REFACTOR subagent tests on skill documentation with fixture worktrees.

Updated Oct 25, 2025
One-click install
npx skills add https://github.com/WesleyMFrederick/cc-workflows --skill testing-skills-with-subagents-wesleymfrederick
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: testing-skills-with-subagents
Source: https://github.com/WesleyMFrederick/cc-workflows/tree/main/.claude/skills/testing-skills-with-subagents
Command: npx skills add https://github.com/WesleyMFrederick/cc-workflows --skill testing-skills-with-subagents-wesleymfrederick

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes evals (resource) and examples (resource) and references (resource) components.

What problem does it solve?

This Skill prevents AI skills from failing to achieve intended behavioral changes by systematically testing them against agent rationalizations and loopholes, especially under pressure.

Core Features & Use Cases

  • TDD for Skills: Applies Test-Driven Development (RED-GREEN-REFACTOR) to skill documentation, ensuring effectiveness and compliance.
  • Pressure Scenarios: Guides you in creating realistic scenarios with combined pressures (time, sunk cost, exhaustion) to rigorously test agent behavior.
  • Loophole Closing: Systematically identifies and plugs rationalization loopholes, making skills "bulletproof" against agent bypass.

Quick Start

Use the testing-skills-with-subagents skill to create an evaluation for my 'create-git-commit' skill.

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 skill documentation to catch agent rationalization and loopholes?

Test-driven development for skills uses RED-GREEN-REFACTOR cycles with subagent-based testing to expose and close rationalization loopholes. RED tests run without skill access to establish baseline behavior, GREEN tests verify skill effectiveness, and REFACTOR iterations tighten prompt wording to eliminate bypass routes.

What are pressure scenarios and why do they matter for skill validation?

Pressure scenarios combine realistic stressors—time constraints, sunk costs, exhaustion—to rigorously test whether agents rationalize away skill instructions under stress. They systematically reveal behavioral gaps that benign testing misses.

Can I apply TDD testing methodology to my own AI skill documentation?

Yes. Define baseline and skill-enabled test prompts from your scenario specifications, run sandboxed subagent evaluations with deny-path restrictions, log results in structured format, and iterate until prompts are bulletproof against agent workarounds.

What components do I need to set up for skill evaluation testing?

Extract Instructions for Sub-Agent into baseline-prompt.md and green-prompt.md files, create scenario.md-driven test specifications, configure fixture worktrees for isolated execution, and set up per-skill jsonl logging directories to capture compliance results.

How do I ensure my test prompts don't contaminate each other across runs?

Isolate baseline and green prompts in separate files, use sandboxed execution environments with deny-path restrictions, and maintain independent logging per test phase to prevent cross-contamination and preserve reproducibility.

What's the difference between RED and GREEN tests in skill validation?

RED tests establish baseline agent behavior without skill access, exposing natural rationalization patterns. GREEN tests measure skill effectiveness by running the same scenarios with skill instructions enabled, quantifying the behavioral delta.