Codebase-to-docs generator for AI coding agents

What to build

A CLI + CI/git-hook tool that scans a codebase on every commit and auto-generates (then keeps in sync) a set of agent-readable context files — architecture map, coding conventions, and a decision log — formatted for Claude Code, Cursor, and similar AI coding agents. Targeted at solo developers and small teams who currently hand-maintain a CLAUDE.md or AGENTS.md file and watch it go stale.

AI coding agents re-derive project context every session because they have no persistent memory; the opportunity is a lightweight layer that turns the repo itself into always-current, agent-formatted documentation instead of relying on memory features or manually-updated markdown files.

Demand

Solo developers and small teams running Claude Code or Cursor daily are the buyers — they're the ones hitting repeated context-loss errors and currently patching it with manual CLAUDE.md/AGENTS.md files, which is exactly the pain the HN discussion surfaced.

• Hacker NewsEngagement

  "Agents don't need memory, they need documentation" — 67 points, 51 comments on HN; high engagement at the source.

• Signal cluster: Agents don't need memory, they need documentationNews

  Argues durable documentation is a more tractable fix for agent context loss than session memory; scored 0.56 with no historical match found.

Stack

• Git hooks (pre-commit/post-commit)
• GitHub Actions / GitLab CI
• Tree-sitter (code parsing for architecture maps)
• Claude API (summarization/decision-log generation)
• Markdown/MDX output targeting CLAUDE.md and AGENTS.md conventions
• SQLite or flat-file store for decision-log history

Solo + AI difficulty

The MVP — a CLI that parses a repo with Tree-sitter, calls an LLM to summarize architecture and conventions into a CLAUDE.md-style file, and wires a git hook to re-run on commit — is buildable solo in 2-4 weeks. The hard part is avoiding staleness/false-confidence on large or fast-changing repos and making the diffing (what actually needs re-summarizing) cheap enough to run on every commit without burning API budget.

Entry threshold

Buildable by one developer in 1-3 weeks using existing LLM APIs to parse and summarize repos into structured docs, plus a sync mechanism tied to commits; no licences or capital needed, but requires good prompt engineering to make summaries genuinely useful across many codebases.

Window

6-12 months

Where to find first users

• Hacker News launch (Show HN)
• r/ClaudeAI and r/cursor
• Product Hunt launch
• Claude Code / Cursor community Discords

Competitors

• DeepWiki
• Swimm
• Mintlify
• Repomix

Counter-signals & risks

• Major agent vendors (Anthropic, Cursor/Anysphere, OpenAI) could ship native persistent memory or project-context features directly into their tools, commoditizing or obsoleting a third-party documentation layer.

• Keeping generated documentation in sync with a fast-changing codebase via git hooks/CI is a known hard problem (staleness, merge conflicts, false confidence from outdated docs) that could undermine trust in the tool's output.

• Solo developers and small teams may be price-sensitive and reluctant to adopt another CI-integrated tool, preferring lightweight conventions (README, CLAUDE.md/AGENTS.md files) they maintain manually over a dedicated product.