# graphify **Repository Path**: maylag/graphify ## Basic Information - **Project Name**: graphify - **Description**: AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph. - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: v8 - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-05-25 - **Last Updated**: 2026-05-26 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

Type `/graphify` in your AI coding assistant and it maps your entire project — code, docs, PDFs, images, videos — into a knowledge graph you can query instead of grepping through files. Works in Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, VS Code Copilot Chat, Aider, OpenClaw, Factory Droid, Trae, Hermes, Kimi Code, Kiro, Pi, and Google Antigravity. ``` /graphify . ``` That's it. You get three files: ``` graphify-out/ ├── graph.html open in any browser — click nodes, filter, search ├── GRAPH_REPORT.md the highlights: key concepts, surprising connections, suggested questions └── graph.json the full graph — query it anytime without re-reading your files ``` For a readable architecture page with Mermaid call-flow diagrams, run: ```bash graphify export callflow-html ``` --- ## Prerequisites | Requirement | Minimum | Check | Install | |---|---|---|---| | Python | 3.10+ | `python --version` | [python.org](https://www.python.org/downloads/) | | uv *(recommended)* | any | `uv --version` | `curl -LsSf https://astral.sh/uv/install.sh \| sh` | | pipx *(alternative)* | any | `pipx --version` | `pip install pipx` | **macOS quick install (Homebrew):** ```bash brew install python@3.12 uv ``` **Windows quick install:** ```powershell winget install astral-sh.uv ``` **Ubuntu/Debian:** ```bash sudo apt install python3.12 python3-pip pipx # or install uv: curl -LsSf https://astral.sh/uv/install.sh | sh ``` --- ## Install > **Official package:** The PyPI package is `graphifyy` (double-y). Other `graphify*` packages on PyPI are not affiliated. The CLI command is still `graphify`. **Step 1 — install the package:** ```bash # Recommended (uv puts graphify on PATH automatically): uv tool install graphifyy # Alternatives: pipx install graphifyy pip install graphifyy ``` **Step 2 — register the skill with your AI assistant:** ```bash graphify install ``` That's it. Open your AI assistant and type `/graphify .` > **PowerShell note:** Use `graphify .` not `/graphify .` — the leading slash is a path separator in PowerShell. > **`graphify: command not found`?** Use `uv tool install graphifyy` or `pipx install graphifyy` — both put the CLI on PATH automatically. With plain `pip`, add `~/.local/bin` (Linux) or `~/Library/Python/3.x/bin` (Mac) to your PATH, or run `python -m graphify`. ### Pick your platform | Platform | Install command | |----------|----------------| | Claude Code (Linux/Mac) | `graphify install` | | Claude Code (Windows) | `graphify install --platform windows` | | Codex | `graphify install --platform codex` | | OpenCode | `graphify install --platform opencode` | | GitHub Copilot CLI | `graphify install --platform copilot` | | VS Code Copilot Chat | `graphify vscode install` | | Aider | `graphify install --platform aider` | | OpenClaw | `graphify install --platform claw` | | Factory Droid | `graphify install --platform droid` | | Trae | `graphify install --platform trae` | | Trae CN | `graphify install --platform trae-cn` | | Gemini CLI | `graphify install --platform gemini` | | Hermes | `graphify install --platform hermes` | | Kimi Code | `graphify install --platform kimi` | | Kiro IDE/CLI | `graphify kiro install` | | Pi coding agent | `graphify install --platform pi` | | Cursor | `graphify cursor install` | | Google Antigravity | `graphify antigravity install` | > Codex users: also add `multi_agent = true` under `[features]` in `~/.codex/config.toml`. > Codex uses `$graphify` instead of `/graphify`. ### Optional extras Install only what you need: | Extra | What it adds | Install | |---|---|---| | `pdf` | PDF extraction | `pip install "graphifyy[pdf]"` | | `office` | `.docx` and `.xlsx` support | `pip install "graphifyy[office]"` | | `google` | Google Sheets rendering | `pip install "graphifyy[google]"` | | `video` | Video/audio transcription (faster-whisper + yt-dlp) | `pip install "graphifyy[video]"` | | `mcp` | MCP stdio server | `pip install "graphifyy[mcp]"` | | `neo4j` | Neo4j push support | `pip install "graphifyy[neo4j]"` | | `svg` | SVG graph export | `pip install "graphifyy[svg]"` | | `leiden` | Leiden community detection (Python < 3.13 only) | `pip install "graphifyy[leiden]"` | | `ollama` | Ollama local inference | `pip install "graphifyy[ollama]"` | | `openai` | OpenAI / OpenAI-compatible APIs | `pip install "graphifyy[openai]"` | | `gemini` | Google Gemini API | `pip install "graphifyy[gemini]"` | | `bedrock` | AWS Bedrock (uses IAM, no API key) | `pip install "graphifyy[bedrock]"` | | `sql` | SQL schema extraction | `pip install "graphifyy[sql]"` | | `all` | Everything above | `pip install "graphifyy[all]"` | --- ## Make your assistant always use the graph Run this once in your project after building a graph: | Platform | Command | |----------|---------| | Claude Code | `graphify claude install` | | Codex | `graphify codex install` | | OpenCode | `graphify opencode install` | | GitHub Copilot CLI | `graphify copilot install` | | VS Code Copilot Chat | `graphify vscode install` | | Aider | `graphify aider install` | | OpenClaw | `graphify claw install` | | Factory Droid | `graphify droid install` | | Trae | `graphify trae install` | | Trae CN | `graphify trae-cn install` | | Cursor | `graphify cursor install` | | Gemini CLI | `graphify gemini install` | | Hermes | `graphify hermes install` | | Kimi Code | `graphify install --platform kimi` | | Kiro IDE/CLI | `graphify kiro install` | | Pi coding agent | `graphify pi install` | | Google Antigravity | `graphify antigravity install` | This writes a small config file that tells your assistant to consult the knowledge graph for codebase questions — preferring scoped queries like `graphify query ""` over reading the full report or grepping raw files. On platforms that support payload-bearing hooks (Claude Code, Gemini CLI), a hook fires automatically before search-style tool calls and nudges your assistant toward the graph path. On the others (Codex, OpenCode, Cursor, etc.), the persistent instruction files (`AGENTS.md`, `.cursor/rules/`, etc.) provide the same query-first guidance. `GRAPH_REPORT.md` is still available for broad architecture review. To remove graphify from all platforms at once: `graphify uninstall` (add `--purge` to also delete `graphify-out/`). Or use the per-platform command (e.g. `graphify claude uninstall`). --- ## What's in the report - **God nodes** — the most-connected concepts in your project. Everything flows through these. - **Surprising connections** — links between things that live in different files or modules. Ranked by how unexpected they are. - **The "why"** — inline comments (`# NOTE:`, `# WHY:`, `# HACK:`), docstrings, and design rationale from docs are extracted as separate nodes linked to the code they explain. - **Suggested questions** — 4–5 questions the graph is uniquely positioned to answer. - **Confidence tags** — every inferred relationship is marked `EXTRACTED`, `INFERRED`, or `AMBIGUOUS`. You always know what was found vs guessed. --- ## What files it handles | Type | Extensions | |------|-----------| | Code (31 languages) | `.py .ts .js .jsx .tsx .mjs .go .rs .java .c .cpp .h .hpp .rb .cs .kt .scala .php .swift .lua .luau .zig .ps1 .ex .exs .m .mm .jl .vue .svelte .astro .groovy .gradle .dart .v .sv .sql .f .f90 .f95 .f03 .f08 .pas .pp .dpr .dpk .lpr .inc .dfm .lfm .lpk .sh .bash .json` | | Docs | `.md .mdx .qmd .html .txt .rst .yaml .yml` | | Office | `.docx .xlsx` (requires `pip install graphifyy[office]`) | | Google Workspace | `.gdoc .gsheet .gslides` (opt-in; requires `gws` auth and `--google-workspace`; Sheets need `pip install graphifyy[google]`) | | PDFs | `.pdf` | | Images | `.png .jpg .webp .gif` | | Video / Audio | `.mp4 .mov .mp3 .wav` and more (requires `pip install graphifyy[video]`) | | YouTube / URLs | any video URL (requires `pip install graphifyy[video]`) | Code is extracted locally with no API calls (AST via tree-sitter). Everything else goes through your AI assistant's model API. Google Drive for desktop `.gdoc`, `.gsheet`, and `.gslides` files are shortcut pointers, not document content. To include native Google Docs, Sheets, and Slides in a headless extraction, install and authenticate the [`gws` CLI](https://github.com/googleworkspace/cli), then run: ```bash pip install "graphifyy[google]" # needed for Google Sheets table rendering gws auth login -s drive graphify extract ./docs --google-workspace ``` You can also set `GRAPHIFY_GOOGLE_WORKSPACE=1`. Graphify exports shortcuts into `graphify-out/converted/` as Markdown sidecars, then extracts those files. --- ## Common commands ```bash /graphify . # build graph for current folder /graphify ./docs --update # re-extract only changed files /graphify . --cluster-only # rerun clustering without re-extracting /graphify . --cluster-only --resolution 1.5 # more granular communities /graphify . --cluster-only --exclude-hubs 99 # suppress utility super-hubs from god-node rankings /graphify . --no-viz # skip the HTML, just the report + JSON /graphify . --wiki # build a markdown wiki from the graph graphify export callflow-html # Mermaid architecture/call-flow HTML (auto-regenerates on every git commit if hook is installed) /graphify query "what connects auth to the database?" /graphify path "UserService" "DatabasePool" /graphify explain "RateLimiter" /graphify add https://arxiv.org/abs/1706.03762 # fetch a paper and add it /graphify add # transcribe and add a video graphify hook install # auto-rebuild on git commit graphify merge-graphs a.json b.json # combine two graphs graphify prs # PR dashboard: CI state, review status, worktree mapping graphify prs 42 # deep dive on PR #42 with graph impact graphify prs --triage # AI ranks your review queue (uses whatever backend is configured) graphify prs --conflicts # PRs sharing graph communities — merge-order risk ``` See the [full command reference](#full-command-reference) below. --- ## Ignoring files Create a `.graphifyignore` in your project root — same syntax as `.gitignore`, including `!` negation: ``` # .graphifyignore node_modules/ dist/ *.generated.py # only index src/, ignore everything else * !src/ !src/** ``` --- ## Team setup `graphify-out/` is meant to be committed to git so everyone on the team starts with a map. **Recommended `.gitignore` additions:** ``` graphify-out/manifest.json # mtime-based, breaks after git clone graphify-out/cost.json # local only # graphify-out/cache/ # optional: commit for speed, skip to keep repo small ``` **Workflow:** 1. One person runs `/graphify .` and commits `graphify-out/`. 2. Everyone pulls — their assistant reads the graph immediately. 3. Run `graphify hook install` to auto-rebuild after each commit (AST only, no API cost). This also sets up a git merge driver so `graph.json` is never left with conflict markers — two devs committing in parallel get their graphs union-merged automatically. 4. When docs or papers change, run `/graphify --update` to refresh those nodes. --- ## Using the graph directly ```bash # query the graph from the terminal graphify query "show the auth flow" graphify query "what connects DigestAuth to Response?" --graph graphify-out/graph.json # expose the graph as an MCP server (for repeated tool-call access) python -m graphify.serve graphify-out/graph.json # register with Kimi Code: kimi mcp add --transport stdio graphify -- python -m graphify.serve graphify-out/graph.json ``` The MCP server gives your assistant structured access: `query_graph`, `get_node`, `get_neighbors`, `shortest_path`, `list_prs`, `get_pr_impact`, `triage_prs`. > **WSL / Linux note:** Ubuntu ships `python3`, not `python`. Use a venv to avoid conflicts: > ```bash > python3 -m venv .venv && .venv/bin/pip install "graphifyy[mcp]" > ``` --- ## Environment variables These are only needed for **headless / CI extraction** (`graphify extract`). When running via the `/graphify` skill inside your IDE, the model API is provided by your IDE session — no extra keys needed. | Variable | Used for | When required | |---|---|---| | `ANTHROPIC_API_KEY` | Claude (Anthropic) backend | `--backend claude` | | `GEMINI_API_KEY` or `GOOGLE_API_KEY` | Google Gemini backend | `--backend gemini` | | `OPENAI_API_KEY` | OpenAI or OpenAI-compatible APIs | `--backend openai` | | `DEEPSEEK_API_KEY` | DeepSeek backend | `--backend deepseek` | | `MOONSHOT_API_KEY` | Kimi Code backend | `--backend kimi` | | `OLLAMA_BASE_URL` | Ollama local inference URL | `--backend ollama` (default: `http://localhost:11434`) | | `OLLAMA_MODEL` | Ollama model name | `--backend ollama` (default: auto-detect) | | `GRAPHIFY_OLLAMA_NUM_CTX` | Override Ollama KV-cache window size | optional — auto-sized by default | | `GRAPHIFY_OLLAMA_KEEP_ALIVE` | Minutes to keep Ollama model loaded | optional — set `0` to unload after each chunk | | `AWS_*` / `~/.aws/credentials` | AWS Bedrock — standard credential chain | `--backend bedrock` (no API key, uses IAM) | | `GRAPHIFY_MAX_WORKERS` | AST parallelism thread count | optional — also `--max-workers` flag | | `GRAPHIFY_MAX_OUTPUT_TOKENS` | Raise output cap for dense corpora | optional — e.g. `32768` for large files | | `GRAPHIFY_API_TIMEOUT` | HTTP timeout in seconds (default: 600) | optional — also `--api-timeout` flag | | `GRAPHIFY_FORCE` | Force graph rebuild even with fewer nodes | optional — also `--force` flag | | `GRAPHIFY_GOOGLE_WORKSPACE` | Auto-enable Google Workspace export | optional — set to `1` | | `GRAPHIFY_TRIAGE_BACKEND` | Backend for `graphify prs --triage` | optional — auto-detected from available keys | | `GRAPHIFY_TRIAGE_MODEL` | Model override for triage | optional — e.g. `claude-opus-4-7` | --- ## Privacy - **Code files** — processed locally via tree-sitter. Nothing leaves your machine. - **Video / audio** — transcribed locally with faster-whisper. Nothing leaves your machine. - **Docs, PDFs, images** — sent to your AI assistant for semantic extraction (via the `/graphify` skill, using whatever model your IDE session runs). Headless `graphify extract` requires `GEMINI_API_KEY` / `GOOGLE_API_KEY` (Gemini), `MOONSHOT_API_KEY` (Kimi), `ANTHROPIC_API_KEY` (Claude), `OPENAI_API_KEY` (OpenAI), `DEEPSEEK_API_KEY` (DeepSeek), a running Ollama instance (`OLLAMA_BASE_URL`), AWS credentials via the standard provider chain (Bedrock - no API key needed, uses IAM), or the `claude` CLI binary (Claude Code - no API key needed, uses your Claude subscription). The `--dedup-llm` flag uses the same key. - No telemetry, no usage tracking, no analytics. --- ## Troubleshooting **`graphify: command not found` after `pip install graphifyy`** pip installs scripts to a user bin directory that may not be on your PATH. Fix: - macOS: add `~/Library/Python/3.x/bin` to your PATH in `~/.zshrc` - Linux: add `~/.local/bin` to your PATH in `~/.bashrc` - Or use `uv tool install graphifyy` / `pipx install graphifyy` — both manage PATH automatically. **`python -m graphify` works but `graphify` command doesn't** Your shell's PATH doesn't include the Python scripts directory. Use `uv` or `pipx` instead of plain `pip`. **`/graphify .` causes "path not recognized" in PowerShell** PowerShell treats a leading `/` as a path separator. Use `graphify .` (no slash) on Windows. **Graph has fewer nodes after `--update` or rebuild** If a refactor deleted files, the old nodes linger. Pass `--force` (or set `GRAPHIFY_FORCE=1`) to overwrite even when the rebuild has fewer nodes. **Graph has duplicate nodes for the same entity (ghost duplicates)** This happens when semantic and AST extraction disagreed on the node ID format. Run a full re-extract to clean up: ```bash graphify extract . --force ``` **Ollama runs out of VRAM / context window exceeded** The KV-cache window is auto-sized but may be too large for your GPU. Reduce it: ```bash GRAPHIFY_OLLAMA_NUM_CTX=8192 graphify extract ./docs --backend ollama --token-budget 4000 ``` **Graph HTML is too large to open in a browser (>5000 nodes)** Skip HTML generation and use the JSON directly: ```bash graphify cluster-only ./my-project --no-viz graphify query "..." ``` **`graph.json` has conflict markers after two devs commit at once** Run `graphify hook install` — it sets up a git merge driver that union-merges `graph.json` automatically so conflicts never happen. **Extraction returns empty nodes/edges for docs or PDFs** Docs and PDFs require an LLM call. Check that your API key is set and the backend is correct: ```bash ANTHROPIC_API_KEY=sk-... graphify extract ./docs --backend claude ``` **Skill version mismatch warning in your IDE** Your installed graphify version is different from the skill file. Update: ```bash uv tool upgrade graphifyy graphify install # overwrites the skill file ``` --- ## Full command reference ``` /graphify # run on current directory /graphify ./raw # run on a specific folder /graphify ./raw --mode deep # more aggressive relationship extraction /graphify ./raw --update # re-extract only changed files /graphify ./raw --directed # preserve edge direction /graphify ./raw --cluster-only # rerun clustering on existing graph /graphify ./raw --no-viz # skip HTML visualization /graphify ./raw --obsidian # generate Obsidian vault /graphify ./raw --wiki # build agent-crawlable markdown wiki /graphify ./raw --svg # export graph.svg /graphify ./raw --graphml # export for Gephi / yEd /graphify ./raw --neo4j # generate cypher.txt for Neo4j /graphify ./raw --neo4j-push bolt://localhost:7687 /graphify ./raw --watch # auto-sync as files change /graphify ./raw --mcp # start MCP stdio server /graphify add https://arxiv.org/abs/1706.03762 /graphify add /graphify add https://... --author "Name" --contributor "Name" /graphify query "what connects attention to the optimizer?" /graphify query "..." --dfs --budget 1500 /graphify path "DigestAuth" "Response" /graphify explain "SwinTransformer" graphify uninstall # remove from all platforms in one shot graphify uninstall --purge # also delete graphify-out/ graphify hook install # post-commit + post-checkout hooks graphify hook uninstall graphify hook status graphify claude install / uninstall graphify codex install / uninstall graphify opencode install graphify cursor install / uninstall graphify gemini install / uninstall graphify copilot install / uninstall graphify aider install / uninstall graphify claw install / uninstall graphify droid install / uninstall graphify trae install / uninstall graphify trae-cn install / uninstall graphify hermes install / uninstall graphify kiro install / uninstall graphify antigravity install / uninstall graphify extract ./docs # headless LLM extraction for CI (no IDE needed) graphify extract ./docs --backend gemini # explicit backend: gemini, kimi, claude, openai, deepseek, ollama, bedrock, or claude-cli graphify extract ./docs --backend gemini --model gemini-3.1-pro-preview graphify extract ./docs --backend ollama # local Ollama (set OLLAMA_BASE_URL / OLLAMA_MODEL) - no API key needed for loopback GRAPHIFY_OLLAMA_NUM_CTX=32768 graphify extract ./docs --backend ollama # override KV-cache window (auto-sized by default) GRAPHIFY_OLLAMA_KEEP_ALIVE=0 graphify extract ./docs --backend ollama # unload model after each chunk (saves VRAM on small GPUs) graphify extract ./docs --backend bedrock # AWS Bedrock via IAM - no API key, uses AWS credential chain graphify extract ./docs --backend claude-cli # route through Claude Code CLI - no API key, uses your Claude subscription graphify extract ./docs --max-workers 16 # AST parallelism (also GRAPHIFY_MAX_WORKERS) graphify extract ./docs --token-budget 30000 # smaller semantic chunks for local/small models graphify extract ./docs --max-concurrency 2 # fewer parallel LLM calls (useful for local inference) graphify extract ./docs --api-timeout 900 # longer HTTP timeout for slow local models (default 600s) graphify extract ./docs --google-workspace # export .gdoc/.gsheet/.gslides via gws before extraction graphify extract ./docs --no-cluster # raw extraction only, skip clustering graphify extract ./docs --force # overwrite graph.json even if new graph has fewer nodes (use after refactors or to clear ghost duplicates) graphify extract ./docs --dedup-llm # LLM tiebreaker for ambiguous entity pairs (uses same API key) graphify extract ./docs --global --as myrepo # extract and register into the cross-project global graph GRAPHIFY_MAX_OUTPUT_TOKENS=32768 graphify extract ./docs --backend claude # raise output cap for dense corpora graphify export callflow-html # graphify-out/-callflow.html graphify export callflow-html --max-sections 8 # cap generated architecture sections graphify export callflow-html --output docs/arch.html graphify export callflow-html ./some-repo/graphify-out graphify global add graphify-out/graph.json myrepo # register a project graph into ~/.graphify/global.json graphify global remove myrepo # remove a project from the global graph graphify global list # show all registered repos + node/edge counts graphify global path # print path to the global graph file graphify prs # PR dashboard: CI, review, worktree, graph impact graphify prs 42 # deep dive on PR #42 graphify prs --triage # AI triage ranking (auto-detects backend from env) graphify prs --worktrees # worktree → branch → PR mapping graphify prs --conflicts # PRs sharing graph communities (merge-order risk) graphify prs --base main # filter to PRs targeting a specific base branch graphify prs --repo owner/repo # run against a different GitHub repo GRAPHIFY_TRIAGE_BACKEND=kimi graphify prs --triage # use a specific backend for triage graphify clone https://github.com/karpathy/nanoGPT graphify merge-graphs a.json b.json --out merged.json graphify --version # print installed version graphify watch ./src graphify check-update ./src graphify update ./src graphify update ./src --no-cluster # skip reclustering, write raw AST graph only graphify update ./src --force # overwrite even if new graph has fewer nodes graphify cluster-only ./my-project graphify cluster-only ./my-project --graph path/to/graph.json # custom graph location graphify cluster-only ./my-project --resolution 1.5 # more, smaller communities graphify cluster-only ./my-project --exclude-hubs 99 # exclude p99 degree nodes from partitioning ``` --- ## Learn more - [How it works](docs/how-it-works.md) — the extraction pipeline, community detection, confidence scoring, benchmarks - [ARCHITECTURE.md](ARCHITECTURE.md) — module breakdown, how to add a language - [Optional integrations](docs/docker-mcp-sqlite.md) — Docker MCP Toolkit + SQLite --- ## Built on graphify — Penpax [**Penpax**](https://graphifylabs.ai) is the always-on layer built on top of graphify — it applies the same graph approach to your entire working life: meetings, browser history, emails, files, and code, updating continuously in the background. Built for people whose work lives across hundreds of conversations and documents they can never fully reconstruct. No cloud, fully on-device. **Free trial launching soon.** [Join the waitlist →](https://graphifylabs.ai) ---

Contributing

### Development setup Clone the repo and install in editable mode: ```bash git clone https://github.com/safishamsi/graphify.git cd graphify git checkout v8 # active development branch # Create a virtual environment (Python 3.10+ required): python3 -m venv .venv source .venv/bin/activate # Windows: .venv\Scripts\activate # Install in editable mode with all optional extras: pip install -e ".[all]" ``` Verify the editable install: ```bash graphify --version python -c "import graphify; print(graphify.__file__)" ``` ### Running tests ```bash pip install pytest pytest tests/ -q # run the full suite pytest tests/test_extract.py -q # one module pytest tests/ -q -k "python" # filter by name ``` > macOS note: the test suite includes both `sample.f90` and `sample.F90` fixtures. These collide on case-insensitive HFS+ / APFS file systems. Run on Linux or in a Docker container if you need to test both Fortran variants simultaneously. ### Git workflow - Active development happens on the `v8` branch. - Commit style: `fix: ` / `feat: ` / `docs: ` - Before opening a PR, run `pytest tests/ -q` and confirm it passes. - Add a fixture file to `tests/fixtures/` and tests to `tests/test_languages.py` for any new language extractor. ### What to contribute **Worked examples** are the most useful contribution. Run `/graphify` on a real corpus, save the output to `worked/{slug}/`, write an honest `review.md` covering what the graph got right and wrong, and open a PR. **Extraction bugs** — open an issue with the input file, the cache entry (`graphify-out/cache/`), and what was missed or wrong. See [ARCHITECTURE.md](ARCHITECTURE.md) for module responsibilities and how to add a language.