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Pydantic Models Py

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Content generator
  • Software development
  • MIT
  • Low risk
  • Has scripts
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From the author

Create 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.
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to defining data models in Python applications using Pydantic v2. It promotes a multi-model pattern that separates concerns by defining distinct classes for base attributes, creation requests, update requests, API responses, and database persistence. By following this pattern, developers can ensure consistent data validation, clean API contracts, and maintainable codebases.

What it does

  • Defines a multi-model pattern including Base, Create, Update, Response, and InDB variants.
  • Provides templates for consistent model structure across API and database layers.
  • Demonstrates how to implement camelCase aliases for frontend compatibility.
  • Guides the creation of optional update fields for partial resource modifications.
  • Outlines integration steps for organizing models within a backend project structure.
  • Includes best practices for Pydantic v2 validation and serialization.

When to use it

  • When designing API request and response schemas for a Python backend.
  • When defining database document structures that require specific metadata.
  • When you need to enforce strict data validation across different application layers.
  • When migrating or starting a new project using Pydantic v2.

Advantages

  • Ensures consistent data contracts between backend and frontend.
  • Reduces code duplication by using a shared Base model.
  • Improves maintainability by separating creation, update, and response logic.
  • Facilitates easier integration with TypeScript-based frontend applications.

Usage examples

“Create a set of Pydantic models for a User resource using the multi-model pattern.”
The agent generates a file containing UserBase, UserCreate, UserUpdate, UserResponse, and UserInDB classes, ensuring all fields are correctly typed and configured.
“How do I define an update model where all fields are optional?”
The agent provides a code snippet using Optional type hints and Field(None) to ensure the update model allows partial updates.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/pydantic-models-py/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip pydantic-models-py.zip -d .agents/skills

Documentation by Microsoft

Pydantic Models

Create Pydantic models following the multi-model pattern for clean API contracts.

Quick Start

Copy the template from assets/template.py and replace placeholders:

  • {{ResourceName}} → PascalCase name (e.g., Project)

  • {{resource_name}} → snake_case name (e.g., project)

Multi-Model Pattern

ModelPurpose
BaseCommon fields shared across models
CreateRequest body for creation (required fields)
UpdateRequest body for updates (all optional)
ResponseAPI response with all fields
InDBDatabase document with doc_type

camelCase Aliases

from datetime import datetime

from pydantic import BaseModel, ConfigDict, Field

class MyModel(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    workspace_id: str = Field(..., alias="workspaceId")
    created_at: datetime = Field(..., alias="createdAt")

Optional Update Fields

class MyUpdate(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    name: Optional[str] = Field(None, min_length=1)
    description: Optional[str] = None

Database Document

class MyInDB(MyResponse):
    doc_type: str = "my_resource"

Integration Steps

  1. Create models in src/backend/app/models/

  2. Export from src/backend/app/models/__init__.py

  3. Add corresponding TypeScript types

Reference Files

FileContents
references/capabilities.mdAdditional non-hero capabilities, operation-group coverage, and production checklists.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-sdk-python/skills/pydantic-models-py · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download pydantic-models-py.zip