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understand-explain

Use when you need a deep-dive explanation of a specific file, function, or module in the codebase
⚡ Productivity skills By Egonex-AI Version v1.0.0 Added 2026-10-06 Updated 2026-10-06 Source ↗
9.0Overall rating
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0Downloads
85.4kStars

Installation

🤖 Install via AI

Copy the prompt below and send it to your AI assistant (e.g. Claude Code) — it will follow the instructions and install automatically.

Install the "understand-explain" skill by following the instructions at https://skill123.me/install/understand-explain.
⌨️ Command line install

Run in your terminal — downloads and installs to ~/.claude/skills/.

curl -fsSL https://skill123.me/install/understand-explain.sh | bash
📦 Download ZIP

Download the zip and extract it into your skills directory (e.g. ~/.claude/skills/), then restart your session.

⬇ Download v1.0.0 · 2 KB
📊 Static rating
9.0/10
Trigger
9.0
Structure
0.0
Workflow
8.0
Content
0.0
Engineering
0.0
Security
10.0

Six-dimension rubric with reviewer rationale.

View scorecard ↓
🛡 Dynamic test
—

Not live-tested yet — this skill is rated on static analysis only.

About this skill

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

/understand-explain

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

Documentation

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

/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.

View full documentation

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

Score breakdown

Trigger
9.0
Structure
0.0
Workflow
8.0
Content
0.0
Engineering
0.0
Security
10.0