skills/testing/testing-agents-with-subagents/SKILL.md
Test agents via subagents: known inputs, captured outputs, verification.
npx skillsauth add notque/claude-code-toolkit testing-agents-with-subagentsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill applies TDD methodology to agent development — RED (observe failures), GREEN (fix agent definition), REFACTOR (edge cases and robustness) — with subagent dispatch as the execution mechanism.
Test what the agent DOES, not what the prompt SAYS. Evidence-based verification only: capture exact outputs from subagent dispatch, verify every prompt change through testing. Always test via the Task tool, always test via the Task tool rather than reading prompts.
Minimum test counts vary by agent type: Reviewer agents need 6 cases (2 real issues, 2 clean, 1 edge, 1 ambiguous), Implementation agents 5 cases (2 typical, 1 complex, 1 minimal, 1 error), Analysis agents 4 cases (2 standard, 1 edge, 1 malformed), Routing/orchestration 4 cases (2 correct route, 1 ambiguous, 1 invalid). No agent is simple enough to skip testing — get human confirmation before exempting any agent.
Each test runs in a fresh subagent to avoid context pollution. After any fix, re-run ALL test cases to catch regressions. One fix at a time — you cannot determine what changed the outcome with multiple simultaneous fixes.
| Signal | Load These Files | Why |
|---|---|---|
| example-driven tasks, errors | examples-and-errors.md | Loads detailed guidance from examples-and-errors.md. |
| implementation patterns | testing-patterns.md | Loads detailed guidance from testing-patterns.md. |
Goal: Read the agent definition and understand what it claims to do before writing tests.
Step 1: Read the agent file
# Read agent definition
cat agents/{agent-name}.md
# Read any referenced skills
cat skills/{skill-name}/SKILL.md
Step 2: Identify testable claims
Extract concrete, testable behaviors from the agent definition:
Step 3: Determine minimum test count
| Agent Type | Minimum Tests | Required Coverage | |------------|---------------|-------------------| | Reviewer agents | 6 | 2 real issues, 2 clean, 1 edge, 1 ambiguous | | Implementation agents | 5 | 2 typical, 1 complex, 1 minimal, 1 error | | Analysis agents | 4 | 2 standard, 1 edge, 1 malformed | | Routing/orchestration | 4 | 2 correct route, 1 ambiguous, 1 invalid |
No gate — this phase is preparation. Move directly to Phase 1.
Goal: Run agent with test inputs and document exact current behavior before any changes.
Step 1: Define test plan
Write the test plan to a file before executing — this creates a reproducible baseline. See ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md for the Test Plan template.
Step 2: Dispatch subagent with test inputs
Use the Task tool to dispatch the agent (see dispatch template in references/examples-and-errors.md). Each test runs in a fresh subagent — this prevents context pollution from earlier tests affecting later ones.
Step 3: Capture results verbatim
Document exact agent outputs. See the verbatim result capture template in references/examples-and-errors.md.
Step 4: Identify failure patterns
Gate: All test cases executed. Exact outputs captured verbatim. Failures documented with specific issues identified. Proceed only when gate passes.
Goal: Update agent definition until all test cases pass. One fix at a time.
Step 1: Prioritize failures
Triage failures by severity — see the Failure Severity table in ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md (Critical/High/Medium/Low).
Step 2: Diagnose root cause
Map the failure type to a fix approach — see the Root Cause → Fix Approach table in references/examples-and-errors.md.
Step 3: Make one fix at a time
Change one thing in the agent definition. Re-run ALL test cases. Document which tests now pass/fail.
Make one fix at a time — you cannot determine which change was effective. Same debugging principle: one variable at a time.
Step 4: Iterate until green
Repeat Step 3 until all test cases pass. If a fix causes a previously passing test to fail, revert and try a different approach. Track fix iterations using the Fix Log template in references/examples-and-errors.md.
Gate: All test cases pass. No regressions from previously passing tests. Can explain what each fix changed and why. Proceed only when gate passes.
Goal: Verify agent handles boundary conditions and produces consistent outputs.
Step 1: Add edge case tests
See the Edge Case Categories table in ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md (Empty / Large / Unusual / Ambiguous inputs).
Step 2: Run consistency tests
Run the same input 3 times. Outputs should be consistent:
If inconsistent: add more explicit instructions to the agent definition. Re-test.
Step 3: Run regression suite
Re-run ALL test cases (original + edge cases) to confirm nothing broke during refactoring.
Step 4: Document final test report
See the Test Report template in ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md.
Gate: Edge cases handled. Consistency verified. Full suite green. Test report documented. Fix is complete.
See ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md for error cases: agent-type-not-found, inconsistent-outputs, subagent-timeout, agent-asks-questions.
See ${CLAUDE_SKILL_DIR}/references/examples-and-errors.md for worked examples: testing a new reviewer agent, testing after agent modification, testing routing logic.
agent-comparison: A/B test agent variantsagent-evaluation: Structural quality checkstest-driven-development: TDD principles applied to agents${CLAUDE_SKILL_DIR}/references/testing-patterns.md: Dispatch patterns, test scenarios, eval harness integration${CLAUDE_SKILL_DIR}/references/examples-and-errors.md: Worked examples (new reviewer, modification, routing) and error handling (agent-not-found, inconsistency, timeout, question-asking)documentation
Document translation: quick/normal/refined modes with chunked parallel subagents and glossary support.
development
AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
testing
Unified voice content generation pipeline with mandatory validation and joy-check. 13-phase pipeline: LOAD, GROUND, STATS-CHECKPOINT, GENERATE, HOOK-GATE, VALIDATE, REFINE, VARIETY-GATE, JOY-CHECK, ANTI-AI, CLOSE-GATE, OUTPUT, CLEANUP. Use when writing articles, blog posts, or any content that uses a voice profile. Use for "write article", "blog post", "write in voice", "generate content", "draft article", "write about".
documentation
Critique-and-rewrite loop for voice fidelity validation.