pydantic-models-py

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 ...

Best use case

pydantic-models-py is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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 ...

Teams using pydantic-models-py should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/pydantic-models-py/SKILL.md --create-dirs "https://raw.githubusercontent.com/ratnesh-maurya/cursor-claude-personas/main/ai-ml-engineer/.claude/skills/pydantic-models-py/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/pydantic-models-py/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How pydantic-models-py Compares

Feature / Agentpydantic-models-pyStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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 ...

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

| Model | Purpose |
|-------|---------|
| `Base` | Common fields shared across models |
| `Create` | Request body for creation (required fields) |
| `Update` | Request body for updates (all optional) |
| `Response` | API response with all fields |
| `InDB` | Database document with `doc_type` |

## camelCase Aliases

```python
class MyModel(BaseModel):
    workspace_id: str = Field(..., alias="workspaceId")
    created_at: datetime = Field(..., alias="createdAt")
    
    class Config:
        populate_by_name = True  # Accept both snake_case and camelCase
```

## Optional Update Fields

```python
class MyUpdate(BaseModel):
    """All fields optional for PATCH requests."""
    name: Optional[str] = Field(None, min_length=1)
    description: Optional[str] = None
```

## Database Document

```python
class MyInDB(MyResponse):
    """Adds doc_type for Cosmos DB queries."""
    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

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

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