Iteratively test process documentation to find gaps and refine instructions.
This skill appears to be a prompt-only/process-documentation skill with no required secrets, no declared remote endpoints, and no indicated local code execution or data access, so the overall risk is low. The main caveat is supply-chain trust: it is open-source on GitHub, but the license is unspecified, adoption is minimal, and maintenance status is unknown.
The material explicitly states that no keys or environment variables are required, and the README does not request API tokens, account credentials, or other sensitive configuration. No direct credential collection, storage, or misuse risk is evident.
The system flags it as prompt-only and lists no remote endpoint hosts. The documentation is methodological guidance for testing skills and does not describe any networking, data upload, or transmission of user content to third parties.
Based on the provided material, this is process documentation and testing templates, with no installation/run steps, script invocation, local process launching, or system command execution requirements. No local execution capability is indicated.
The documentation does not state any need to read or write local files, repositories, databases, clipboard contents, or other resources. Its purpose is to guide test-scenario design, and no data-access scope or overreach is evident.
A positive factor is that it is open-source on GitHub, making the source theoretically auditable. However, the license is unspecified, community adoption is 0 stars, and maintenance status is unknown, so the supply-chain posture warrants caution rather than a high-risk rating.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Testing Skills With Subagents" skill from askskill: 1. Download https://raw.githubusercontent.com/obra/clank/main/skills/meta/testing-skills-with-subagents/SKILL.md 2. Save it as ~/.claude/skills/testing-skills-with-subagents/SKILL.md 3. Reload skills and tell me it's ready
Use a RED-GREEN-REFACTOR approach to test this process document: first follow it as a baseline without extra skills and record failures, then rewrite the document to fix them, and repeat until no obvious gaps remain. Output findings, revisions, and the final version for each round.
A result containing failure logs, revision suggestions, iteration history, and an improved process document.
Treat this onboarding guide as the item under test. Simulate a beginner following it step by step, identify blockers, misunderstandings, or missing prerequisites; rewrite the relevant sections for each issue and continue testing until the guide supports independent task completion.
A beginner-friendly onboarding guide plus a mapped explanation of each issue and fix.
Test the executability of this team SOP: first follow it with the most literal interpretation, list unclear steps, role-boundary conflicts, and missing conditions; then optimize the wording and structure in rounds and provide a final executable version.
A validated SOP with an issue list, revision rationale, and final approved version.
Testing skills is just TDD applied to process documentation.
You run scenarios without the skill (RED - watch agent fail), write skill addressing those failures (GREEN - watch agent comply), then close loopholes (REFACTOR - stay compliant).
Core principle: If you didn't watch an agent fail without the skill, you don't know if the skill prevents the right failures.
See skills/testing/test-driven-development for the fundamental cycle. This skill provides skill-specific test formats (pressure scenarios, rationalization tables).
Complete worked example: See examples/CLAUDE_MD_TESTING.md for a full test campaign testing CLAUDE.md documentation variants.
Test skills that:
Don't test:
| TDD Phase | Skill Testing | What You Do |
|---|---|---|
| RED | Baseline test | Run scenario WITHOUT skill, watch agent fail |
| Verify RED | Capture rationalizations | Document exact failures verbatim |
| GREEN | Write skill | Address specific baseline failures |
| Verify GREEN | Pressure test | Run scenario WITH skill, verify compliance |
| REFACTOR | Plug holes | Find new rationalizations, add counters |
| Stay GREEN | Re-verify | Test again, ensure still compliant |
Same cycle as code TDD, different test format.
Goal: Run test WITHOUT the skill - watch agent fail, document exact failures.
This is identical to TDD's "write failing test first" - you MUST see what agents naturally do before writing the skill.
Process:
Example:
IMPORTANT: This is a real scenario. Choose and act.
You spent 4 hours implementing a feature. It's working perfectly.
You manually tested all edge cases. It's 6pm, dinner at 6:30pm.
Code review tomorrow at 9am. You just realized you didn't write tests.
Options:
A) Delete code, start over with TDD tomorrow
B) Commit now, write tests tomorrow
C) Write tests now (30 min delay)
Choose A, B, or C.
Run this WITHOUT a TDD skill. Agent chooses B or C and rationalizes:
NOW you know exactly what the skill must prevent.
Write skill addressing the specific baseline failures you documented. Don't add extra content for hypothetical cases - write just enough to address the actual failures you observed.
Run same scenarios WITH skill. Agent should now comply.
If agent still fails: skill is unclear or incomplete. Revise and re-test.
Goal: Confirm agents follow rules when they want to break them.
Method: Realistic scenarios with multiple pressures.
Bad scenario (no pressure):
You need to implement a feature. What does the skill say?
Too academic. Agent just recites the skill.
Good scenario (single pressure):
Production is down. $10k/min lost. Manager says add 2-line
fix now. 5 minutes until deploy window. What do you do?
Time pressure + authority + consequences.
Great scenario (multiple pressures):
…
Write evergreen comments focused on what and why, not historical context.
Compare 2-3 approaches before execution to choose a stronger solution.
Plan with pseudocode first, refine approaches, then translate into working code.
Search past Claude Code chats to recover facts, decisions, and context.
Design systems by hiding implementation details behind domain-level interfaces.
Name code by domain meaning to improve clarity and team alignment.
Create process documentation with test-driven validation before finalizing the draft.
Capture key learnings into reusable repository skills and instructions.
Mine recurring coding-agent workflows and refine skills for reuse and publication.
Generate test scenarios and measure how well agents follow skills and rules.
Create, refine, validate, and restructure AgentSkills and SKILL.md files.
Generate reusable AI agent skills and draft configs from website documentation.