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Found 1,474 Skills
Comprehensive guide for building production-ready microservices with FastAPI including REST API patterns, async operations, dependency injection, and deployment strategies
Read and write to Upstash Redis-compatible key-value store via REST API. Use when there is a need to save or retrieve key-value data, use Redis features (caching, counters, lists, sets, hashes, sorted sets, etc.) for the current interaction, or when the user explicitly asks to use Upstash or Redis.
Generates CRUD REST API endpoints with request validation, TypeScript types, consistent response formats, error handling, and documentation. Includes route handlers, validation schemas (Zod/Joi), typed responses, and usage examples. Use when building "REST API", "CRUD endpoints", "API routes", or "backend endpoints".
Perform spatial analysis, geometry operations, and use ArcGIS REST services. Use for routing, geocoding, geoprocessing, elevation analysis, viewshed, and feature queries with statistics.
Master iOS networking - URLSession, async/await, REST APIs, authentication
Resume work from a previous session, restoring context after a break, continuing work after /clear, or picking up where you left off. Triggers include "resume work", "continue work", "pick up where I left off", "restore context", and "resume session".
FastAPI web framework patterns. Triggers on: fastapi, api endpoint, dependency injection, pydantic model, openapi, swagger, starlette, async api, rest api, uvicorn.
API contract design conventions for FastAPI projects with Pydantic v2. Use during the design phase when planning new API endpoints, defining request/response contracts, designing pagination or filtering, standardizing error responses, or planning API versioning. Covers RESTful naming, HTTP method semantics, Pydantic v2 schema naming conventions (XxxCreate/XxxUpdate/XxxResponse), cursor-based pagination, standard error format, and OpenAPI documentation. Does NOT cover implementation details (use python-backend-expert) or system-level architecture (use system-architecture).
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
REST API security hardening with authentication, rate limiting, input validation, security headers. Use for production APIs, security audits, defense-in-depth, or encountering vulnerabilities, injection attacks, CORS issues.
API development expert including REST design, OpenAPI, and documentation
Use when backing up, restoring, or validating golden datasets. Prevents data loss and ensures test data integrity for AI/ML evaluation systems.