warehouse
warehouse is an data AI skill with a core value of Plan and review read-only data warehouse analysis with explicit scope, privacy, provenance, and validation checks. It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Plan and review read-only data warehouse analysis with explicit scope, privacy, provenance, and validation checks.
Quick Facts
mkdir -p ./skills/warehouse && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/warehouse/SKILL.md -o ./skills/warehouse/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
Plan and review read-only data warehouse analysis with explicit scope, privacy, provenance, and validation checks.
🎯 Best For
- Engineering teams doing code reviews
- Open source maintainers
- Claude users
- Data professionals
- Analytics teams
💡 Use Cases
- Reviewing pull requests for security vulnerabilities
- Checking code style consistency
- 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 warehouse 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 skill check for OWASP Top 10?
Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.
How do I install warehouse?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/warehouse/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
Blindly accepting AI suggestions
Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.