name: query-dot-ai description: "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." context: fork agent: Explore allowed-tools:

• Read
• Glob
• Grep
• Bash(grep:*)

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.