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Skills/Documentation
egonex-ai avatar

Understand Explain

egonex-ai/understand-anything

This is for when you're staring at unfamiliar code and need more than a quick summary. It walks through the knowledge graph to find your target file or function, maps out what calls it and what it depends on, figures out which architectural layer it lives in, then reads the actual source and explains it all in context. The approach is methodical: grep first, read strategically, never dump the whole graph into context. What I like here is that it doesn't just explain the code in isolation. It shows you the neighborhood, the data flow, the why-it-exists. Good for onboarding or diving into a gnarly module you need to modify but don't yet understand.

installs
3.9K
GitHub stars
88.4K
last updated
Aug 21, 2026
View on GitHubSave

Install

$ npx -y skills add egonex-ai/understand-anything --skill understand-explain --agent claude-code

Installs into .claude/skills of the current project.

Files

/understand-explain

Provide a thorough, in-depth explanation of a specific code component.

Graph Structure Reference

The knowledge graph JSON has this structure:

  • project — {name, description, languages, frameworks, analyzedAt, gitCommitHash}
  • nodes[] — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
    • Code node types: file, function, class, module, concept
    • Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource
    • Domain/knowledge node types: domain, flow, step, article, entity, topic, claim, source
    • IDs use the node type as prefix, e.g. file:path, function:path:name, config:path, article:path
  • edges[] — each has {source, target, type, direction, weight}
    • Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites
  • layers[] — each has {id, name, description, nodeIds[]}
  • tour[] — each has {order, title, description, nodeIds[]}

How to Read Efficiently

  1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file
  2. Only read sections you need — don't dump the entire graph into context
  3. Node names and summaries are the most useful fields for understanding
  4. Edges tell you how components connect — follow imports and calls for dependency chains

Instructions

  1. Resolve the data directory $UA_DIR. Run UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.

  2. Check graph freshness before using graph-derived context:

    • Read project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
      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 before explaining that graph-derived context may omit those changes. Suggest: Run /understand to refresh the 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. Find the target node — use Grep to search the knowledge graph for the component: "$ARGUMENTS"

    • For file paths (e.g., src/auth/login.ts): search for "filePath" matches
    • For function notation (e.g., src/auth/login.ts:verifyToken): search for the function name in "name" fields filtered by the file path
    • Note the exact node id, type, summary, tags, and complexity
  4. Find all connected edges — Grep for the target node's ID in the edges section:

    • "source" matches → things this node calls/imports/depends on (outgoing)
    • "target" matches → things that call/import/depend on this node (incoming)
    • Note the connected node IDs and edge types
  5. Read connected nodes — for each connected node ID from step 4, Grep for those IDs in the nodes section to get their name, summary, and type. This builds the component's neighborhood.

  6. Identify the layer — Grep for the target node's ID in the "layers" section to find which architectural layer it belongs to and that layer's description.

  7. Read the actual source file — Read the source file at the node's filePath for the deep-dive analysis.

  8. Explain the component in context:

    • Its role in the architecture (which layer, why it exists)
    • Internal structure (functions, classes it contains — from contains edges)
    • External connections (what it imports, what calls it, what it depends on — from edges)
    • Data flow (inputs → processing → outputs — from source code)
    • Explain clearly, assuming the reader may not know the programming language
    • Highlight any patterns, idioms, or complexity worth understanding
SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/egonex-ai/understand-anything
Category
Documentation
First seen
Jun 11, 2026

More from egonex-ai/understand-anything

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  • Understand Diff3.6K
  • Understand Domain3.6K
  • Understand Knowledge3.5K
  • Understand5.3K

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