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pydantic-ai-dependency-injection

Inject external resources into PydanticAI agents using RunContext and deps_type.

Updated Feb 17, 2026
Search Tags:#type safety#python#agent development#dependency injection#pydantic-ai#runcontext
One-click install
npx skills add https://github.com/javierhbr/random-poc --skill pydantic-ai-dependency-injection-javierhbr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pydantic-ai-dependency-injection
Source: https://github.com/javierhbr/random-poc/tree/main/custom-skills/beagle-main/plugins/beagle-ai/skills/pydantic-ai-dependency-injection
Command: npx skills add https://github.com/javierhbr/random-poc --skill pydantic-ai-dependency-injection-javierhbr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill simplifies the management of external resources like database connections, API clients, and user context within PydanticAI agents, ensuring type safety and organized dependency injection.

Core Features & Use Cases

  • Dependency Injection: Easily provide external resources to your agents using RunContext and deps_type.
  • Type Safety: Leverage static analysis and runtime type checking for dependencies and agent outputs.
  • Use Case: When your agent needs to interact with a live database and an external API, define these as dependencies and inject them seamlessly into your agent's tools and instructions.

Quick Start

Use the pydantic-ai-dependency-injection skill to define database and API client dependencies for your agent.

Frequently Asked Questions about pydantic-ai-dependency-injection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I inject external resources like database connections into PydanticAI agents?▼

You inject external resources by defining a deps_type and passing dependencies through RunContext, allowing agent tools and instructions to securely access database connections and API clients.

How does dependency injection work with RunContext in PydanticAI?▼

Dependency injection using RunContext works by providing external resources and user context to agent tools at runtime, ensuring type safety through explicit agent type annotations and runtime validation.

How do I ensure type safety for dependencies and outputs in PydanticAI?▼

Type safety for dependencies and outputs is ensured by leveraging explicit agent type annotations and runtime dependency validation, enabling static analysis to catch type errors before execution.

Can I provide user context and API clients to my agent tools at the same time?▼

Yes, you can provide user context and API clients simultaneously by defining them as dependencies within the specified deps_type, injecting them seamlessly into your agent's tools and instructions.

When do I need dependency injection for my agent development workflow?▼

You need dependency injection when your agent interacts with live databases or external APIs, allowing you to define these external resources as dependencies and inject them seamlessly into tools.

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