Skill Market

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.

GitHub
githubcommunityantigravity-skillsbusiness-knowledgeclaude-codeclaude-skillscodexcodex-skills
0.0
0 installs82.8K GitHub starsby Lum1104

Skill Introduction

Overview
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.

Core value

Turns reusable Debugging know-how into an installable skill, helping users complete github, community, antigravity-skills, business-knowledge work faster.

Target users

  • Developers, testers, and maintainers who handle Debugging tasks in Focus Code.
  • Teams that already trust workflows or content from Lum1104.
  • Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

  • Read the skill content first to confirm required inputs, expected outputs, and dependencies.
  • Try it on a small task before relying on it for critical work.
  • Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
  • For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

  • Tasks related to github, community, antigravity-skills, business-knowledge that need a reusable execution flow.
  • Converting a community repo, team convention, or personal workflow into day-to-day assistance.
  • Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

  • Results depend on the quality of the original skill content and may need human correction.
  • It does not replace code review, tests, security review, or professional judgment.
  • External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

  • Structured around Debugging, making it easier to discover and reuse than loose prompt snippets.
  • Marked as GitHub, which helps users judge trust and maintenance expectations.
  • Keeps the original source link available for repository, documentation, or discussion follow-up.
  • Tagged with github, community, antigravity-skills, business-knowledge, so it can be filtered by concrete task intent.

Install and use

Install
Copy Install Command
focus install understand-domain-523f4b
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Detail Preview

SKILL.md

Primary filemarkdown4 KB

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

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