AI SummaryA comprehensive set of development guidelines and reusable agents for building AI-powered Python applications in Windsurf using Mirascope, covering patterns for LLM integration, component structure, and best practices. Developers building intelligent agents and tools in Python will benefit from these standardized patterns and pre-built components.
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to add the "sygaldry — Windsurf Rules" prompt rules to my project. Repository: https://github.com/greyhaven-ai/sygaldry Please read the repo to find the rules/prompt file, then: 1. Download it to the correct location (.cursorrules, .windsurfrules, .github/prompts/, or project root — based on the file type) 2. If there's an existing rules file, merge the new rules in rather than overwriting 3. Confirm what was added
Description
Discover and integrate reusable agents and tools into your Python projects
Project Context
This is a Sygaldry AI project using Mirascope for LLM integration.
Key Technologies
• Python 3.12+ • Mirascope for LLM calls and prompt templates • Pydantic for data validation and response models • FastAPI for web services • Lilypad for observability (when enabled)
Mirascope Integration
• Use @prompt_template decorators for all prompts • Implement response_model with Pydantic classes • Prefer async patterns: async def for LLM calls • Use functional tools, not class-based tools
Component Structure
Standard sygaldry component with component.json manifest
Discussion
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Works With
Any AI assistant that accepts custom rules or system prompts