— name: understand-domain description: Extract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph. argument-hint: [–full] — # /understand-domain Extracts business domain knowledge — domains, business flows, and process steps — from a codebase and produces an interactive horizontal flow graph in the dashboard. ## How It Works – If a knowledge graph already exists (`.understand-anything/knowledge-graph.json`), derives domain knowledge from it (cheap, no file scanning) – If no knowledge graph exists, performs a lightweight scan: file tree + entry point detection + sampled files – Use `–full` flag to force a fresh scan even if a knowledge graph exists ## Instructions ### Phase 1: Detect Existing Graph 1. Check if `.understand-anything/knowledge-graph.json` exists in the current project 2. If it exists AND `–full` was NOT passed → proceed to Phase 3 (derive from graph) 3. Otherwise → proceed to Phase 2 (lightweight scan) ### Phase 2: Lightweight Scan (Path 1) The preprocessing script does NOT produce a domain graph — it produces **raw material** (file tree, entry points, exports/imports) so the domain-analyzer agent can focus on the actual domain analysis instead of spending dozens of tool calls exploring the codebase. Think of it as a cheat sheet: cheap Python preprocessing → expensive LLM gets a clean, small input → better results for less cost. 1. Run the preprocessing script bundled with this skill: “` python ./extract-domain-context.py <project-root> “` This outputs `<project-root>/.understand-anything/intermediate/domain-context.json` containing: – File tree (respecting `.gitignore`) – Detected entry points (HTTP routes, CLI commands, event handlers, cron jobs, exported handlers) – File signatures (exports, imports per file) – Code snippets for each entry point (signature + first few lines) – Project metadata (package.json, README, etc.) 2. Read the generated `domain-context.json` as context for Phase 4 3. Proceed to Phase 4 ### Phase 3: Derive from Existing Graph (Path 2) 1. Read `.understand-anything/knowledge-graph.json` 2. Format the graph data as structured context: – All nodes with their types, names, summaries, and tags – All edges with their types (especially `calls`, `imports`, `contains`) – All layers with their descriptions – Tour steps if available 3. This is the context for the domain analyzer — no file reading needed 4. Proceed to Phase 4 ### Phase 4: Domain Analysis 1. Read the domain-analyzer agent prompt from `agents/domain-analyzer.md` 2. Dispatch a subagent with the domain-analyzer prompt + the context from Phase 2 or 3 3. The agent writes its output to `.understand-anything/intermediate/domain-analysis.json` ### Phase 5: Validate and Save 1. Read the domain analysis output 2. Validate using the standard graph validation pipeline (the schema now supports domain/flow/step types) 3. If validation fails, log warnings but save what's valid (error tolerance) 4. Save to `.understand-anything/domain-graph.json` 5. Clean up `.understand-anything/intermediate/domain-analysis.json` and `.understand-anything/intermediate/domain-context.json` ### Phase 6: Launch Dashboard 1. Auto-trigger `/understand-dashboard` to visualize the domain graph 2. The dashboard will detect `domain-graph.json` and show the domain view by default