Why use fresh subagent instances for testing?

Fresh instances ensure a clean slate for every test, providing a consistent baseline state and isolating the specific impact of the skill being evaluated.

What are rationalization guardrails?

These are internal logic patterns that prevent the AI from providing post-hoc justifications for errors, ensuring the skill remains robust and follows its intended instructions.

How does the three-phase TDD approach work for skills?

It involves Phase 1 (Red) to establish baseline behavior without the skill, Phase 2 (Green) to measure improvements with the skill loaded, and Phase 3 (Refactor) to test anti-rationalization guardrails.

What is priming bias in Claude Code skills?

Priming bias occurs when previous conversation context influences results, making it difficult to tell if a skill is working effectively or if Claude is simply following recent history.

Subagent Skill Testing

Name: Subagent Skill Testing
Author: athola

byathola

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123

Security & Testing

Validates Claude Code skills using a TDD-style methodology and fresh subagent instances to eliminate priming bias.

About

This skill provides a rigorous framework for testing and validating Claude Code skills by leveraging fresh subagent instances to ensure objective evaluation. It helps developers avoid the 'priming problem' where prior conversation history skews results, allowing for precise measurement of a skill's impact on Claude's behavior. By implementing a three-phase TDD approach—Baseline, With-Skill, and Rationalization—users can systematically confirm that their custom skills are effective, reproducible, and resistant to post-hoc justification.

Key Features

Comparative analysis framework for skill-related metrics
Three-phase TDD methodology (Baseline, With-Skill, Rationalization)
Fresh instance isolation to prevent conversation priming bias
Anti-rationalization guardrail validation and testing
123 GitHub stars
Reproducible testing patterns across diverse scenarios

Use Cases

Measuring the behavioral impact of skill updates during development
Validating the effectiveness of a newly authored Claude Code skill
Testing skill resilience against rationalization and prompt leakage

About

Key Features

Comparative analysis framework for skill-related metrics
Three-phase TDD methodology (Baseline, With-Skill, Rationalization)
Fresh instance isolation to prevent conversation priming bias
Anti-rationalization guardrail validation and testing
123 GitHub stars
Reproducible testing patterns across diverse scenarios

Use Cases

Measuring the behavioral impact of skill updates during development
Validating the effectiveness of a newly authored Claude Code skill
Testing skill resilience against rationalization and prompt leakage