Agent-first, zero-dependency, self-maintaining codebase documentation & change tracking system. LLM-operated wiki with health matrix, semantic record-change, heartbeat monitor, and static dashboard.
Extends Unix tree so every file shows its one-line concern and boundary, giving a separation-of-concerns overview of the whole workspace at a glance. A fast, enforceable map for AI agents.
Review systems and architecture, not code, with chorograph
meta-bonsai generates a pruned ASCII tree that highlights only developer-marked files and directories, keeping ancestor paths to preserve structure.
Local-first context saving for AI coding agents: map first, slice next, retrieve exactly.
Structural analysis for codebases. Produces dependency graphs, class hierarchies, and cross-boundary coupling maps via language plugins -- compressed into token-efficient formats for LLM context windows. Multi-format output including TOON.
Turn your app into a typed knowledge graph AI coding agents query instead of reading source. Rust CLI, MIT.
Interactive visualization tool for AIReady codebase analysis
Your agents break less code and burn fewer tokens — deterministic call/import graph + 27 MCP tools for coding agents. Claude Code plugin & MCP server; zero deps, runs 100% locally.
Reusable engineering skills for AI coding assistants—covering codebase mapping, auditing, architecture, issue scoping, change planning, implementation, optimization, and diagramming.
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