What problem does it solve? Supabase evolves quickly, and outdated training data leads to broken implementations, insecure RLS policies, and subtle auth vulnerabilities. This Skill keeps AI agents aligned with current Supabase documentation, changelogs, and security best practices when building or debugging Supabase projects. ## Core Features & Use Cases - Security checklist enforcement: Catches Supabase-specific traps like user_metadata in JWT authorization, views bypassing RLS, SECURITY DEFINER functions exposed in public schemas, and BOLA/IDOR policy mistakes. - Schema change workflow: Directs agents to iterate with execute_sql or supabase db query, run advisors, then commit clean migrations via supabase db pull. - CLI and MCP guidance: Provides version-aware CLI usage, known gotchas, and step-by-step MCP server troubleshooting. - Use Case: When a user reports that a newly created table is inaccessible via the REST API, the agent checks Data API settings, grants role access, and enables RLS correctly. ## Quick Start Ask the agent to create a new Supabase table with secure RLS policies and expose it to the Data API.
