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supabase-backend

supabase-backend

github.com/abelv22Data & databases080 installsUpdated today
Repository

About supabase-backend

An architecture skill for the iTaxiBcn backend, covering Supabase databases, security, Edge Functions, and SQL. It offers guidance for schema optimization, geospatial operations, and implementation patterns.

Key features

  1. 01Time-series data and index optimization
  2. 02RLS and device-based access security
  3. 03Edge Function performance and error handling
  4. 04SQL migrations and stored procedures
  5. 05PostGIS distance and polygon operations

Use cases

  1. 01Optimize location updates and wait-time queries
  2. 02Design device-identifier access controls
  3. 03Improve geofencing Edge Functions
  4. 04Write idempotent migrations and server-side calculations

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/abelv22/project-foundation --skill supabase-backend

After installing, type/supabase-backendin Claude Code to confirm it loaded.

Details

From the project README

Supabase & Backend Architecture Skill

This skill enables the assistant to provide high-level architectural advice and implementation details for the iTaxiBcn backend.

Knowledge Areas

1. Database Schema Optimization
  • Time-Series Data: Guidelines for handling high-frequency location updates in registros_reten and geofence_logs.
  • Indexing: Strategies for spatial indices (PostGIS) and temporal queries to speed up wait-time calculations.
  • Materialized Views: Recommendation for replacing heavy queries on registros_reten with materialized views for zone aggregations.
2. Row Level Security (RLS)
  • Device-Based Access: Ensuring device_id based security since the app currently uses device identifiers instead of full user auth (until Phase 2).
  • Audit Logs: Best practices for geofence_logs and location_debug_logs security.
3. Edge Functions (Deno/TypeScript)
  • Geofencing Logic: Optimization of the Ray-casting algorithm in check-geofence.
  • Performance: Minimizing startup time and memory footprint of edge functions.
  • Error Handling: Robust try-catch patterns and standard JSON responses.
4. SQL Scripting
  • Migrations: Following the supabase/migrations/ structure.
  • Stored Procedures: Writing efficient PL/pgSQL for complex logic like useWhereNext score calculation on the server side.

Guidelines for Responses

  • Always suggest Materialized Views for dashboard metrics that don't need second-by-second accuracy.
  • When writing SQL, ensure idempotency (use CREATE OR REPLACE or IF NOT EXISTS).
  • Prioritize PostGIS functions for distance and polygon math.

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