ai-md
ai-md是一款data方向的AI技能，核心价值是Convert human-written CLAUDE，可用于解决开发者在data领域的实际问题，帮助用户提升效率、自动化重复任务或优化工作流。
Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.
mkdir -p ./skills/ai-md && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/ai-md/SKILL.md -o ./skills/ai-md/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.
🎯 Best For
- QA engineers
- Developers writing unit tests
- Claude users
- Data professionals
- Analytics teams
💡 Use Cases
- Generating test cases for edge conditions
- Writing integration test suites
- Data pipeline auditing
- Query optimization
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply ai-md to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does this generate test mocks?
Many testing skills include mock generation. Check the install command and skill content for details.
How do I install ai-md?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/ai-md/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not testing edge cases
AI tends to generate happy-path tests. Manually review for boundary conditions.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.