subagent-testing

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Test skills via TDD in fresh subagents. Use when validating behavior or preventing bias.

Testing & QA 323 stars 29 forks Updated today MIT

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Skill Content

# Subagent Testing - TDD for Skills Test skills with fresh subagent instances to prevent priming bias and validate effectiveness. ## When NOT To Use - Writing the skill under test (use `abstract:skill-authoring`) - A static quality audit with no execution (use `abstract:skills-eval`) ## Table of Contents 1. [Overview](#overview) 2. [Why Fresh Instances Matter](#why-fresh-instances-matter) 3. [Testing Methodology](#testing-methodology) 4. [Quick Start](#quick-start) 5. [Detailed Testing Guide](#detailed-testing-guide) 6. [Success Criteria](#success-criteria) ## Overview **Fresh instances prevent priming:** Each test uses a new Claude conversation to verify the skill's impact is measured, not conversation history effects. ## Why Fresh Instances Matter ### The Priming Problem Running tests in the same conversation creates bias: - Prior context influences responses - Skill effects get mixed with conversation history - Can't isolate skill's true impact ### Fresh Instance Benefits - **Isolation**: Each test starts clean - **Reproducibility**: Consistent baseline state - **Measurement**: Clear before/after comparison - **Validation**: Proves skill effectiveness, not priming ## Testing Methodology Three-phase TDD-style approach: ### Phase 1: Baseline Testing (RED) Test without skill to establish baseline behavior. ### Phase 2: With-Skill Testing (GREEN) Test with skill loaded to measure improvements. ### Phase 3: Rationalization Testing (REFACTOR) Test skill's anti-rat...

Details

Author
athola
Repository
athola/claude-night-market
Created
8 months ago
Last Updated
today
Language
Python
License
MIT

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