kitty

Build a code relationship graph with tree-sitter and SQLite for semantic queries.

1|Updated Mar 28, 2026
One-click install
npx skills add https://github.com/Kakise/cartographing-kitties-plugin --skill kitty-kakise
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kitty
Source: https://github.com/Kakise/cartographing-kitties-plugin/tree/main/plugins/kitty/skills/kitty
Command: npx skills add https://github.com/Kakise/cartographing-kitties-plugin --skill kitty-kakise

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Cartographing Kittens provides structural understanding of codebases by parsing with tree-sitter, building a graph of relationships, and exposing an MCP server for agent-driven analysis.

Core Features & Use Cases

  • AST-powered codebase intelligence for structural questions (definitions, imports, relationships) and for navigating large codebases.
  • Blast radius and dependency analysis using graph traversal to understand impact and changes.
  • Semantic search enabled by annotated summaries and tags across the codegraph, improving discovery over plain text search.
  • Agent-driven workflows (brainstorm, plan, work, review) orchestrating multi-agent pipelines to ship features.

Quick Start

Index the codebase and start exploring the structure with kitty:explore.

Frequently Asked Questions about kitty

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

FAQPage Schema
How do I analyze codebase structure and map dependencies in Python and TypeScript projects?▼

Codebase structure analysis is performed by parsing source files with tree-sitter to build a relationship graph, enabling dependency mapping and blast radius analysis across Python, TypeScript, and JavaScript projects.

How does graph-based code exploration work for navigating large codebases?▼

Graph-based code exploration works by using tree-sitter to parse syntax trees and storing relationships in a SQLite graph, allowing you to query definitions, imports, and connections to navigate large codebases.

What's the best way to perform blast radius analysis when modifying code imports?▼

Blast radius analysis is executed by traversing the relationship graph to trace dependency impacts, allowing you to understand the downstream effects of modifying imports and definitions before making changes.

Can I use MCP-based workflows for agent-driven code exploration and feature planning?▼

MCP-based workflows are supported by exposing an MCP server for agent-driven analysis, orchestrating multi-agent pipelines to brainstorm, plan, work, and review features directly against the codegraph.

Does semantic search across a codegraph improve discovery over plain text search?▼

Semantic search across a codegraph improves discovery by using annotated summaries and tags applied to graph nodes, providing contextual structural matches that go beyond plain text search results.

When do I need tree-sitter parsing and SQLite graph storage for codebase analysis?▼

Tree-sitter parsing and SQLite graph storage are needed when you require structural understanding of definitions and imports, enabling AST-powered queries and dependency mapping rather than simple text matching.