subagent-testing
Test skills via TDD in fresh subagents. Use when validating behavior or preventing bias.
Works with
--- name: subagent-testing description: Test skills via TDD in fresh subagents. Use when validating behavior or preventing bias. license: MIT --- # 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-rationalization guardrails. ## Quick Start ```bash # 1. Create baseline tests (without skill) # Use 5 diverse scenarios # Document full responses # 2. Create with-skill tests (fresh instances) # Load skill explicitly # Use identical prompts # Compare to baseline # 3. Create rationalization tests # Test anti-rationalization patterns # Verify guardrails work ``` ## Detailed Testing Guide For complete testing patterns, examples, and templates: - **[Testing Patterns](modules/testing-patterns.md)** - Full TDD methodology - **[Test Examples](modules/testing-patterns.md)** - Baseline, with-skill, rationalization tests - **[Analysis Templates](modules/testing-patterns.md)** - Scoring and comparison frameworks ## Success Criteria - **Baseline**: Document 5+ diverse baseline scenarios - **Improvement**: ≥50% improvement in skill-related metrics - **Consistency**: Results reproducible across fresh instances - **Rationalization Defense**: Guardrails prevent ≥80% of rationalization attempts ## See Also - **skill-authoring**: Creating effective skills - **bulletproof-skill**: Anti-rationalization patterns - **test-skill**: Automated skill testing command ## Exit Criteria - [ ] Baseline (RED) phase documents at least 5 diverse scenarios run in fresh Claude instances without the skill active, with full response text recorded. - [ ] With-skill (GREEN) phase uses identical prompts in new fresh instances (not continuations of the baseline conversation) and shows >= 50% improvement on skill-related metrics. - [ ] Rationalization (REFACTOR) phase shows skill guardrails blocking >= 80% of rationalization attempts tested across at least 3 pressure scenarios. - [ ] Results are reproducible: the same prompts in a new fresh instance produce consistent outcomes, confirming the effect is not conversation-history priming.
More Testing skills
tdd
mattpocock/skills
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
setup-pre-commit
mattpocock/skills
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

