testing-skills-with-subagents

Test skills with subagents under pressure scenarios and log rationalizations.

4|Updated Dec 7, 2020
One-click install
npx skills add https://github.com/charly3pins/dotfiles --skill testing-skills-with-subagents-charly3pins
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: testing-skills-with-subagents
Source: https://github.com/charly3pins/dotfiles/tree/main/.config/opencode/skills/testing-skills-with-subagents
Command: npx skills add https://github.com/charly3pins/dotfiles --skill testing-skills-with-subagents-charly3pins

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Skills often fail to achieve their intended purpose because agents find loopholes or rationalize away compliance, especially under pressure, leading to ineffective automation.

Core Features & Use Cases

  • TDD for Skills: Applies the Red-Green-Refactor cycle to skill documentation, ensuring robust and compliant agent behavior.
  • Pressure Scenario Testing: Guides creating realistic scenarios with multiple pressures (time, sunk cost, authority) to test skill resilience.
  • Rationalization Plugging: Systematically identifies and counters agent rationalizations, closing loopholes in skill design.
  • Use Case: After writing a new skill, use this to rigorously test it with subagents under various pressures, documenting and addressing every rationalization until the skill is bulletproof and ensures consistent agent compliance.

Quick Start

I have created a new skill. Help me test it using subagents and pressure scenarios to ensure it resists rationalization.

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 a skill to ensure agents won't rationalize away compliance?

Test skills with subagents under pressure scenarios—combining time constraints, sunk-cost pressure, and authority pressure—to surface rationalizations. Document every loophole agents find, refactor the skill to close it, and re-test until the skill consistently enforces intended behavior without workarounds.

What is TDD for skills and how does it apply to AI agent behavior?

TDD for skills applies Red-Green-Refactor cycles to skill documentation: write a failing test scenario where agents rationalize noncompliance (RED), refactor the skill to block that rationalization (GREEN), and verify repeatable compliance (REFACTOR). This ensures skills withstand pressure and remain robust across deployments.

How do I create pressure scenarios that expose agent rationalization?

Combine 3 or more pressure types—time limits, sunk-cost framing, authority constraints—in a single scenario. Run the skill with subagents under these pressures, capture rationalization attempts in logs, and identify which skill language or constraints failed. Use these findings to tighten skill wording and enforcement.

Can I use this to validate skills before deployment?

Yes. Run baseline tests without the skill to establish noncompliant behavior, then test with the skill under realistic pressures. Verify GREEN outcomes (compliant behavior) and REFACTOR outcomes (documented skill improvements) before deployment to ensure consistent, compliant agent performance.

What's the best way to systematically close loopholes in skill design?

Log every rationalization agents attempt during pressure tests. For each loophole, update skill language to explicitly block that rationalization path, then re-test with subagents. Repeat until no new rationalizations emerge and compliance metrics stabilize across all pressure combinations.

Do I need documentation standards or compliance frameworks to use this approach?

No specific framework is required, but clear skill documentation improves testability. The process itself enforces compliance by iteratively tightening skill language based on actual agent behavior under pressure, making vague or exploitable instructions visible and fixable.