Pydantic Validation
Skill Verified ActivePython data validation using type hints and runtime type checking with Pydantic v2's Rust-powered core for high-performance validation in FastAPI, Django, and configuration management.
To provide developers with a thorough guide and practical examples for implementing robust data validation in Python applications using Pydantic.
Features
- Python data validation with Pydantic v2
- Runtime type checking and coercion
- API request/response validation
- Settings and configuration management
- SQLAlchemy and Django integration patterns
- Comprehensive code examples and best practices
Use Cases
- Validating API request and response bodies
- Parsing and validating configuration files or environment variables
- Ensuring data integrity in Python projects
- Implementing type-safe data classes with automatic validation
Non-Goals
- Directly performing data validation actions
- Replacing Pydantic library itself
- Providing runtime validation services
Practices
- Data Validation
- Type Hinting
- Schema Definition
Installation
npx skills add bobmatnyc/claude-mpm-skillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedSimilar Extensions
Senior Fullstack
99Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scoring, and stack selection guidance. Use when the user asks to "scaffold a new project", "create a Next.js app", "set up FastAPI with React", "analyze code quality", "audit my codebase", "what stack should I use", "generate project boilerplate", or mentions fullstack development, project setup, or tech stack comparison.
Python Best Practices
99Python/FastAPI coding standards including async patterns, Pydantic v2, SQLAlchemy 2.0, and project structure. Use when writing Python code, reviewing FastAPI projects, or learning FastAPI conventions.
Celery
98Distributed task queue system for Python enabling asynchronous execution of background jobs, scheduled tasks, and workflows across multiple workers with Django, Flask, and FastAPI integration.
FastAPI Expert
98Use 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 documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.
Pydantic Models Py
97Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.
API Security Review Skill
94API security checklist for reviewing endpoints before deployment. Use when creating or modifying API routes to ensure proper authentication, authorization, and input validation.