dot-ai-query-dot-ai
Query sibling dot-ai projects to verify features are USABLE (not just defined). IMPORTANT: When calling this skill, explain HOW you plan to use the feature (e.g., 'I need to call X via REST API from the UI' or 'I need to import Y function'). This helps verify the full chain from definition to exposure.
适合你，如果需要在开发中确认功能不仅定义而且可用
npx oh-my-skill add vfarcic/dot-ai-cli/dot-ai-query-dot-aicurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- vfarcic/dot-ai-cli/dot-ai-query-dot-ainpx oh-my-skill verify vfarcic/dot-ai-cli/dot-ai-query-dot-ai怎么用
技能原文 SKILL.md
Query dot-ai Projects
Explore the dot-ai ecosystem codebases to find the requested information.
Project Locations
Sibling projects are located in the parent directory of the current working directory (../):
- dot-ai - Main MCP server (API endpoints, tools, handlers)
- dot-ai-ui - Web UI for visualizations and dashboard
- dot-ai-controller - Kubernetes controller
- dot-ai-stack - Stack deployment configs
- dot-ai-website - Documentation website
Default to dot-ai (MCP server) if the target project is unclear.
Important: Do NOT use this skill to query the project you're currently working in. Use local tools (Read, Grep, Glob) instead.
Excluded
dot-ai-infra - Production infrastructure. Only query if user explicitly requests it.
Verification Mindset
Don't just find that something EXISTS - prove it's USABLE.
- Finding a type/interface is NOT enough
- Finding internal code is NOT enough
- You must trace from definition → implementation → exposure
When asked "does X exist?", answer:
- "Yes, and here's how to use it: [concrete usage]" OR
- "It exists internally but is NOT exposed for external use"
Go deep, not wide. Follow the code path until you can prove how the caller would actually use the feature.