Validate runtime data with Pydantic v2 models and settings.
npx skills add https://github.com/gao-hongnan/omniagents --skill pydantic-gao-hongnan
Please help me install this Agent Skill. Skill: pydantic Source: https://github.com/gao-hongnan/omniagents/tree/main/plugins/python/skills/pydantic Command: npx skills add https://github.com/gao-hongnan/omniagents --skill pydantic-gao-hongnan
This skill addresses the fragility of untyped data handling by enforcing strict, runtime validation at system boundaries, preventing deployment errors and data corruption.
Use the pydantic skill to refactor the current module by replacing all dict-based data structures with strict Pydantic v2 models and adding appropriate validation logic.
High-intent search queries and answers about installing and using this skill.
Enforce strict runtime validation for API payloads by replacing loose dictionaries with Pydantic v2 BaseModel structures, ensuring incoming JSON strictly adheres to your schema before reaching business logic.
Securely handle configuration in Python backend services by using Pydantic BaseSettings to load environment variables, enforcing strict schema validation and secure secret handling at system boundaries.
Implement cross-field constraints and discriminated unions for complex event payloads by applying Pydantic v2 advanced validation patterns, including field_validator and model_validate, to enforce data integrity.
The best way to refactor untyped dictionary data structures is replacing them with immutable Pydantic v2 value objects, preventing deployment errors and data corruption through strict schema enforcement.
Yes, this approach requires adherence to Pydantic v2 API patterns, specifically utilizing model_validate for instantiation, field_validator for custom logic, and BaseSettings for configuration management.
You need strict schema enforcement for untyped data when refactoring API request handlers or configuration loaders to prevent fragility, ensuring data validity before processing within your application.
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