PRP Template for Pydantic AI Agents

use-cases/template-generator/PRPs/INITIAL_PYDANTIC_AI.md

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+# Template Generation Request
+
+## TECHNOLOGY/FRAMEWORK:
+
+**Example:** CrewAI multi-agent systems  
+
+**Your technology:** Pydantic AI agents
+
+---
+
+## TEMPLATE PURPOSE:
+
+**What specific use case should this template be optimized for?**
+
+**Your purpose:** Building intelligent AI agents with tool integration, conversation handling, and structured data validation using Pydantic AI framework
+
+---
+
+## CORE FEATURES:
+
+**What are the essential features this template should help developers implement?**
+
+**Your core features:**
+
+- Agent creation with different model providers (OpenAI, Anthropic, Gemini)
+- Tool integration patterns (web search, file operations, API calls)
+- Conversation memory and context management
+- Structured output validation with Pydantic models
+- Error handling and retry mechanisms
+- Testing patterns for AI agent behavior
+
+---
+
+## EXAMPLES TO INCLUDE:
+
+**What working examples should be provided in the template?**
+
+**Your examples:**
+
+- Basic chat agent with memory
+- Tool-enabled agent (web search + calculator)
+- Multi-step workflow agent
+- Agent with custom Pydantic models for structured outputs
+- Testing examples for agent responses and tool usage
+
+---
+
+## DOCUMENTATION TO RESEARCH:
+
+**What specific documentation should be thoroughly researched and referenced?**
+
+**Your documentation:**
+- https://ai.pydantic.dev/ - Official Pydantic AI documentation
+- Model provider APIs (OpenAI, Anthropic) for integration patterns
+- Tool integration best practices and examples
+
+---
+
+## DEVELOPMENT PATTERNS:
+
+**What specific development patterns, project structures, or workflows should be researched and included?**
+
+**Your development patterns:**
+- How to structure agent modules and tool definitions
+- Configuration management for different model providers
+- Environment setup for development vs production
+- Logging and monitoring patterns for AI agents
+
+---
+
+## SECURITY & BEST PRACTICES:
+
+**What security considerations and best practices are critical for this technology?**
+
+**Your security considerations:**
+- API key management
+- Input validation and sanitization for agent inputs
+- Rate limiting and usage monitoring
+- Prompt injection prevention
+- Cost control and monitoring for model usage
+
+---
+
+## COMMON GOTCHAS:
+
+**What are the typical pitfalls, edge cases, or complex issues developers face with this technology?**
+
+**Your gotchas:**
+- Handling model provider rate limits and errors
+- Managing conversation state across requests
+- Tool execution error handling and retries
+
+---
+
+## VALIDATION REQUIREMENTS:
+
+**What specific validation, testing, or quality checks should be included in the template?**
+
+**Your validation requirements:**
+- Tool unit testing testing
+- Agent unit testing