# What Is the Domain View and How Is It Extracted with /understand-domain? > Discover the Domain View a code-level business structure graph. Learn how Egonex AI extracts it using the /understand-domain skill and LLM reasoning. - Repository: [Egonex/Understand-Anything](https://github.com/Egonex-AI/Understand-Anything) - Tags: how-to-guide - Published: 2026-06-12 --- **The Domain view is a horizontal flow graph that visualizes the high-level business structure of a codebase, including logical domains, inter-domain flows, and process steps, extracted via the `/understand-domain` skill through a six-phase pipeline that scans source code and applies LLM reasoning.** The `Egonex-AI/Understand-Anything` repository provides an AI-powered architecture analysis tool that generates two primary perspectives on your codebase: the low-level structural view and the business-level **Domain view**. When you invoke the `/understand-domain` skill, the system orchestrates a multi-phase extraction pipeline that transforms raw source files into a [`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json) file, enabling rapid architectural insight without the noise of implementation details. ## Understanding the Domain View The **Domain view** abstracts away file-level complexity to reveal how business concepts interact. It consists of three core elements: - **Domains** – Logical business areas such as *Payments*, *User Management*, or *Inventory* - **Flows** – Data or action movements between domains, showing dependencies and interactions - **Steps** – Individual processes or operations that comprise a flow This representation appears by default in the Understand-Anything dashboard, offering stakeholders a clear picture of system architecture without requiring them to navigate source code. ## How /understand-domain Extracts the Domain View The skill executes a six-phase pipeline defined in [`understand-anything-plugin/skills/understand-domain/SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-domain/SKILL.md). Each phase handles specific concerns, from filesystem scanning to LLM-powered analysis. ### Phase 0: Resolve Project Root The system first determines the real repository root, including work-tree handling, to ensure generated files write to the correct location. According to the source code, this logic lives in [`SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/SKILL.md) lines 19-38. ### Phase 1: Detect Existing Graph The skill checks for a pre-existing [`knowledge-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/knowledge-graph.json) file. If found and the `--full` flag is not supplied, the extraction **derives** domain data directly from the existing graph, avoiding expensive file I/O. This optimization is implemented in [`SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/SKILL.md) lines 89-94. ### Phase 2: Lightweight Scan When no prior graph exists or `--full` is specified, the bundled Python script **[`extract-domain-context.py`](https://github.com/Egonex-AI/Understand-Anything/blob/main/extract-domain-context.py)** executes. This scanner: 1. Walks the source tree respecting `.gitignore` patterns 2. Detects entry points (HTTP routes, CLI commands, cron jobs) 3. Samples a subset of files to collect exports and imports 4. Reads project-level metadata (e.g., [`package.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/package.json), `README`) The output is written to `/.understand-anything/intermediate/domain-context.json`. The core implementation spans lines 1-429 in [`extract-domain-context.py`](https://github.com/Egonex-AI/Understand-Anything/blob/main/extract-domain-context.py). ### Phase 3: Derive from Knowledge Graph If a [`knowledge-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/knowledge-graph.json) is present, the skill converts the node/edge data into the context format expected by the domain analyzer, bypassing the filesystem scan entirely. This logic appears in [`SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/SKILL.md) lines 112-121. ### Phase 4: Domain Analysis The **`domain-analyzer`** agent (prompt stored in [`agents/domain-analyzer.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/agents/domain-analyzer.md)) receives the context from Phase 2 or 3. It applies LLM reasoning to identify business domains, map flows between them, and define operational steps, emitting a structured [`domain-analysis.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-analysis.json). This phase is documented in [`SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/SKILL.md) lines 124-128. ### Phase 5: Validate and Save The output undergoes validation against the graph schema, which now includes `domain`, `flow`, and `step` types. The final artifact is saved as **[`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json)** under `.understand-anything/`. The constant `DOMAIN_GRAPH_FILE` in [`core/src/persistence/index.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/core/src/persistence/index.ts) (line 150) defines this output path. ### Phase 6: Dashboard Launch The dashboard auto-loads [`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json). In [`dashboard/vite.config.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/dashboard/vite.config.ts) (lines 252, 299-300), the development server routes requests to serve this file, and the UI displays the **Domain view** by default, with an option to switch to the *Structural view*. ## Running the /understand-domain Skill You can trigger the extraction through the chat interface or manually invoke components for debugging. ### Basic Usage Reuse an existing knowledge graph if available: ```text /understand-domain ``` Force a fresh lightweight scan: ```text /understand-domain --full ``` ### Manual Preprocessing For debugging or custom pipelines, run the scanner directly: ```bash # From the repository root python ./understand-anything-plugin/skills/understand-domain/extract-domain-context.py ``` This produces `/.understand-anything/intermediate/domain-context.json`. ### Inspecting Results View the generated domain graph: ```bash cat /.understand-anything/domain-graph.json | jq . ``` The JSON structure contains top-level arrays: `domains`, `flows`, and `steps`, each with `id`, `name`, `description`, and linking fields (`source`, `target`). ## Key Implementation Files | File | Role | |------|------| | [`understand-anything-plugin/skills/understand-domain/SKILL.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-domain/SKILL.md) | Orchestrates all six phases of the extraction pipeline | | [`understand-anything-plugin/skills/understand-domain/extract-domain-context.py`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-domain/extract-domain-context.py) | Lightweight filesystem scanner that builds [`domain-context.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-context.json) | | [`understand-anything-plugin/packages/core/src/persistence/index.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/packages/core/src/persistence/index.ts) | Persists the final [`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json) (constant `DOMAIN_GRAPH_FILE`) | | [`understand-anything-plugin/packages/dashboard/vite.config.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/packages/dashboard/vite.config.ts) | Serves [`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json) to the frontend and selects the Domain view by default | | [`understand-anything-plugin/agents/domain-analyzer.md`](https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/agents/domain-analyzer.md) | LLM prompt that transforms raw context into structured domain graphs | ## Summary - The **Domain view** represents business architecture as domains, flows, and steps, distinct from code-level structure. - The `/understand-domain` skill executes a **six-phase pipeline** that resolves project roots, detects existing graphs, performs lightweight scans, and applies LLM analysis. - Extraction leverages **[`extract-domain-context.py`](https://github.com/Egonex-AI/Understand-Anything/blob/main/extract-domain-context.py)** for filesystem sampling and the **`domain-analyzer`** agent for business logic identification. - Output is stored as **[`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json)** and automatically served to the dashboard via [`vite.config.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/vite.config.ts) routes. - The system optimizes performance by **deriving domain data from existing knowledge graphs** when available, avoiding redundant file I/O. ## Frequently Asked Questions ### What is the difference between Domain view and Structural view? The **Domain view** displays horizontal business flows between logical domains like *Payments* and *User Management*, while the **Structural view** shows the vertical hierarchy of files, folders, and code dependencies. The Domain view targets architectural decisions, whereas the Structural view aids implementation navigation. ### How does the lightweight scan work without reading all files? The **[`extract-domain-context.py`](https://github.com/Egonex-AI/Understand-Anything/blob/main/extract-domain-context.py)** script uses intelligent sampling to detect entry points (HTTP routes, CLI commands) and reads only exported symbols and metadata files. It respects `.gitignore` patterns and projects the business structure from a representative subset rather than parsing every line of code, making it fast even on large repositories. ### Where is the domain graph data stored? The final output is saved as **[`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json)** in the `.understand-anything/` directory at your project root. This path is defined by the `DOMAIN_GRAPH_FILE` constant in [`core/src/persistence/index.ts`](https://github.com/Egonex-AI/Understand-Anything/blob/main/core/src/persistence/index.ts) (line 150). Intermediate context data resides in [`.understand-anything/intermediate/domain-context.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/.understand-anything/intermediate/domain-context.json). ### Can I run the extraction manually without the AI skill? Yes. You can invoke the Python scanner directly: `python extract-domain-context.py `. This generates the intermediate context JSON without LLM processing. However, to produce the final [`domain-graph.json`](https://github.com/Egonex-AI/Understand-Anything/blob/main/domain-graph.json), you must either run the full skill (which triggers the `domain-analyzer` agent) or manually execute the analysis phase with the appropriate LLM prompt.