4,642,764 AI resources indexedWorking toward the world’s largest AI resource index.
Reusable instructions for compatible AI agents.
Field counts come from the latest full-catalog snapshot. A resource can belong to several fields and platforms.
Database and data management conventions for all projects using databases. Covers schema migrations, backup strategy, data lifecycle, index management, and connection pooling. Applied when designing, implementing, or reviewing database interactions.
Develop lightweight Flask APIs with routing, blueprints, database integration, authentication, and request/response handling. Use when building RESTful APIs, microservices, or lightweight web services with Flask.
Avoid common Flask mistakes — context errors, circular imports, session configuration, and production gotchas.
An MCP server that provides on-demand skill loading for AI coding assistants.
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
Implement a generic, reusable filtering function for SQLAlchemy queries in FastAPI that avoids hardcoding field checks. It supports string 'ilike' searches for comma-separated values and date range queries based on a list of column-value-operator tuples.
Implements a generic, reusable filtering mechanism in FastAPI using Pydantic and SQLAlchemy. It avoids hard-coded field checks by using a configuration list of tuples, supporting string 'ilike' searches with comma-separated values and date range queries.
Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documenta...
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and
Implements database layers using Prisma, Drizzle ORM, TypeORM, SQLAlchemy 2.0, GORM, Diesel, Entity Framework Core 8, Hibernate/Panache, ActiveRecord, Ecto, Sequelize, Kysely, and Knex. Covers migrations, connection pooling, read replicas, query optimization, transaction management, and database ...
Try a broader search or clear some filters.
Platform labels describe intended use. Read each resource's author credits, requirements and available access methods.