AI SummaryIntent Kit provides Cursor rules for building hierarchical intent-driven Python workflows with LLMs, enabling developers to create structured, context-aware automation systems. It's useful for developers building complex AI-driven applications that require intent classification and conditional execution.
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to add the "intent-kit — Cursor Rules" prompt rules to my project. Repository: https://github.com/Stephen-Collins-tech/intent-kit 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
A Python library for building intent-driven workflows with LLMs
Project Overview
Intent Kit is a Python library for building hierarchical intent classification and execution systems. It provides a tree-based intent architecture with classifier and action nodes, supports multiple AI service backends, and enables context-aware execution.
Code Examples
• Keep examples simple, realistic, and focused. • Always include error handling in examples. • Document all assumptions and prerequisites for running examples.
Documentation Examples
• Ensure all code examples are tested and runnable. • Keep examples updated with API changes. • Provide expected outputs where it aids understanding.
Python Code
• Use Python 3.11+ features and type hints throughout. • Follow PEP 8 with 4-space indentation. • Use descriptive variable and function names. • Prefer composition over inheritance. • Use dataclasses for data structures. • Add comprehensive docstrings for all public classes, methods, and functions (Google-style). • Use type hints for all function parameters and return values.
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Works With
Any AI assistant that accepts custom rules or system prompts