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subagent-testing

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

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包含的文件(2)

  • SKILL.md3.3 KB
  • modules/testing-patterns.md13.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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)

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

# 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:

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
  • 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.

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