MCPInstall

understand-domain

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.

Installs
3.6K
Last 24h
+30
Trending rank
#4350
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/egonex-ai/understand-anything --skill understand-domain
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads understand-domain automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

/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 (.ua/knowledge-graph.json, or the legacy .understand-anything/knowledge-graph.json when that directory is present), 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 0: Resolve PROJECT_ROOT

Set PROJECT_ROOT to the current working directory.

Worktree redirect. If PROJECT_ROOT is inside a git worktree (not the main checkout), redirect output to the main repository root. Worktrees managed by Claude Code are ephemeral — the data directory (.ua/, or legacy .understand-anything/) written there is destroyed when the session ends, taking the domain graph with it (issue #133). Detect a worktree by comparing git rev-parse --git-dir against git rev-parse --git-common-dir; in a normal checkout or submodule they resolve to the same path, in a worktree they differ and the parent of --git-common-dir is the main repo root.

COMMON_DIR=$(git -C "$PROJECT_ROOT" rev-parse --git-common-dir 2>/dev/null)
GIT_DIR=$(git -C "$PROJECT_ROOT" rev-parse --git-dir 2>/dev/null)
if [ -n "$COMMON_DIR" ] && [ -n "$GIT_DIR" ]; then
  COMMON_ABS=$(cd "$PROJECT_ROOT" && cd "$COMMON_DIR" 2>/dev/null && pwd -P)
  GIT_ABS=$(cd "$PROJECT_ROOT" && cd "$GIT_DIR" 2>/dev/null && pwd -P)
  if [ -n "$COMMON_ABS" ] && [ "$COMMON_ABS" != "$GIT_ABS" ]; then
    MAIN_ROOT=$(dirname "$COMMON_ABS")
    if [ -d "$MAIN_ROOT" ] && [ "${UNDERSTAND_NO_WORKTREE_REDIRECT:-0}" != "1" ]; then
      echo "[understand-domain] Detected git worktree at $PROJECT_ROOT"
      echo "[understand-domain] Redirecting output to main repo root: $MAIN_ROOT"
      echo "[understand-domain] (Set UNDERSTAND_NO_WORKTREE_REDIRECT=1 to keep PROJECT_ROOT as the worktree.)"
      PROJECT_ROOT="$MAIN_ROOT"
    fi
  fi
fi

Use $PROJECT_ROOT (not the bare CWD) for every reference to "the current project" / <project-root> in subsequent phases.

Resolve the data directory $UA_DIR. All Understand-Anything artifacts live in the project's data directory. Resolve it once, now that $PROJECT_ROOT is known, and reuse $UA_DIR for every read and write in later phases:

UA_DIR="$PROJECT_ROOT/$([ -d "$PROJECT_ROOT/.understand-anything" ] && echo .understand-anything || echo .ua)"

This keeps the legacy .understand-anything/ directory when it already exists (existing projects keep working with no migration) and uses the new .ua/ otherwise. Because each phase may run in a fresh shell, carry $UA_DIR forward like $PROJECT_ROOT, re-resolving it with the line above if a later command block needs it.

Important: do not assume the plugin root is simply two directories above the skill path string. In many installations ~/.agents/skills/understand-domain is a symlink into the real plugin checkout. Prefer runtime-provided plugin roots first (for Claude), then fall back to universal symlinks, skill symlink resolution, and common clone-based install paths.

Resolve the plugin root like this:

SKILL_REAL=$(realpath ~/.agents/skills/understand-domain 2>/dev/null || readlink -f ~/.agents/skills/understand-domain 2>/dev/null || echo "")
SELF_RELATIVE=$([ -n "$SKILL_REAL" ] && cd "$SKILL_REAL/../.." 2>/dev/null && pwd || echo "")
COPILOT_SKILL_REAL=$(realpath ~/.copilot/skills/understand-domain 2>/dev/null || readlink -f ~/.copilot/skills/understand-domain 2>/dev/null || echo "")
COPILOT_SELF_RELATIVE=$([ -n "$COPILOT_SKILL_REAL" ] && cd "$COPILOT_SKILL_REAL/../.." 2>/dev/null && pwd || echo "")

PLUGIN_ROOT=""
for candidate in \
  "${CLAUDE_PLUGIN_ROOT}" \
  "$HOME/.understand-anything-plugin" \
  "$SELF_RELATIVE" \
  "$COPILOT_SELF_RELATIVE" \
  "$HOME/.codex/understand-anything/understand-anything-plugin" \
  "$HOME/.opencode/understand-anything/understand-anything-plugin" \
  "$HOME/.pi/understand-anything/understand-anything-plugin" \
  "$HOME/understand-anything/understand-anything-plugin"; do
  if [ -n "$candidate" ] && [ -f "$candidate/package.json" ] && [ -f "$candidate/pnpm-workspace.yaml" ]; then
    PLUGIN_ROOT="$candidate"
    break
  fi
done

if [ -z "$PLUGIN_ROOT" ]; then
  echo "Error: Cannot find the understand-anything plugin root."
  echo "Checked:"
  echo "  - ${CLAUDE_PLUGIN_ROOT:-<unset CLAUDE_PLUGIN_ROOT>}"
  echo "  - $HOME/.understand-anything-plugin"
  echo "  - ${SELF_RELATIVE:-<unresolved path derived from ~/.agents/skills/understand-domain>}"
  echo "  - ${COPILOT_SELF_RELATIVE:-<unresolved path derived from ~/.copilot/skills/understand-domain>}"
  echo "  - $HOME/.codex/understand-anything/understand-anything-plugin"
  echo "  - $HOME/.opencode/understand-anything/understand-anything-plugin"
  echo "  - $HOME/.pi/understand-anything/understand-anything-plugin"
  echo "  - $HOME/understand-anything/understand-anything-plugin"
  echo "Make sure the plugin is installed correctly."
  exit 1
fi

Use $PLUGIN_ROOT for every reference to agent definitions in subsequent phases.

Phase 1: Detect Existing Graph

  1. Check if $UA_DIR/knowledge-graph.json exists
  2. If it exists AND --full was NOT passed, check freshness before deriving from it:
    • Read project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Change to $PROJECT_ROOT, resolve it as a commit before using it in any Git diff, compare the resolved commit with git rev-parse HEAD, and inspect project-scoped committed and working-tree changes:
      GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)
      git rev-parse HEAD
      git diff --name-only "$GRAPH_COMMIT" HEAD -- .
      git diff --cached --name-only -- .
      git diff --name-only -- .
      git ls-files --others --exclude-standard -- .
      
    • The -- . pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty.
    • Ignore the selected data directory (.ua/ or legacy .understand-anything/) in every command's output because it contains generated graph artifacts, not project source drift.
    • If the committed diff or any working-tree command reports project files, warn that domain extraction may omit those changes. Suggest: Run /understand to refresh the knowledge graph.
    • Run the commit diff only when GRAPH_COMMIT_RAW resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
  3. After that preflight, proceed to Phase 3 (derive from graph).
  4. Otherwise, proceed to Phase 2 (lightweight scan). When --full is used, skip this preflight because the command performs a fresh scan instead of consuming the existing graph.

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, passing $PROJECT_ROOT from Phase 0:
    python ./extract-domain-context.py "$PROJECT_ROOT"
    
    This outputs $UA_DIR/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 $UA_DIR/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 $PLUGIN_ROOT/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 $UA_DIR/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 $UA_DIR/domain-graph.json
  5. Clean up $UA_DIR/intermediate/domain-analysis.json and $UA_DIR/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

FAQ

What does the understand-domain skill do?

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.

How do I install understand-domain?

Run npx skills add https://github.com/egonex-ai/understand-anything --skill understand-domain in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/understand-domain/ (personal) or .claude/skills/understand-domain/ (project).

Which AI agents can use understand-domain?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is understand-domain safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains understand-domain?

It is published by egonex-ai in egonex-ai/understand-anything. It has 3,600 recorded installs.

More from egonex-ai/understand-anything

View all →

understand

egonex-ai/understand-anything

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

understand-explain

egonex-ai/understand-anything

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase

understand-dashboard

egonex-ai/understand-anything

Launch the interactive web dashboard to visualize a codebase's knowledge graph

Data & Databases3.8K installs

understand-chat

egonex-ai/understand-anything

Use when you need to ask questions about a codebase or understand code using a knowledge graph

understand-onboard

egonex-ai/understand-anything

Use when you need to generate an onboarding guide for new team members joining a project

3.8K installs

understand-diff

egonex-ai/understand-anything

Use when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks

Popular code quality & workflow skills

View category →

grill-me

mattpocock/skills

A relentless interview to sharpen a plan or design.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

handoff

mattpocock/skills

Compact the current conversation into a handoff document for another agent to pick up.

domain-modeling

mattpocock/skills

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.

codebase-design

mattpocock/skills

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

diagnosing-bugs

mattpocock/skills

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.