Start shipping faster in 10 minutes with automated docs and context rich agents

We use AST parsing and symbol resolution to extract every function, type, class, and variable — and unify cross‑references across languages (SCIP). You get a complete, accurate map of your code with consistent jumps across stacks.

A directed graph of your codebase is topologically sorted from dependencies → dependents (think DB → auth → services → UI). You see how work naturally flows and what changes impact next.

We traverse the graph and use an LLM to write docs for each file/definition: purpose, dependencies, and usage. Because dependencies are summarized first, dependents inherit precise context.

Docs render as Markdown in a minimal React app with React Flow graphs for quick navigation across dependencies. You and new teammates can jump around and understand systems in minutes.

Auto‑refresh on push to main, plus incremental parsing with Merkle tree/hash diffing so only changed parts update — faster, cheaper, monorepo‑ready.

Martin fans out smart queries and traverses matching nodes at once, with citations. You get the right spots to change, fast.

Minimal, cited context (typically 40–60% fewer input tokens). You save money and get cleaner, more accurate suggestions.

New hires hop the graph, read clean docs, and copy known patterns. They ship faster with fewer questions.

DFS for depth, BFS for coverage — we follow edges to where changes actually land so fixes stick the first time.

Impacted dependents and upstream contracts are flagged. You avoid surprise regressions and cut review ping‑pong.