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General coding87k · #844

understand-explain

Helps your agent explain specific code parts. It provides details about a file, function, or module.

What it does

This tool helps you understand specific parts of programming code. It analyzes files, functions, or modules, explaining what they do, how they connect to other parts, and their importance.

When to use it

  • ✓When you encounter a piece of code you don't understand.
  • ✓When trying to figure out how a specific feature works.
  • ✓To learn about the structure of a programming project.

Example of what to ask your AI

“Explain the 'calculate_total_price' function in the 'src/utils/math.js' file.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-explain/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/Egonex-AI/Understand-Anything/blob/main/understand-anything-plugin/skills/understand-explain/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool first checks if the code information is up-to-date. Then, it searches for the code component you requested, analyzes its connections to other parts, and reads the source code to give you a detailed explanation.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add Egonex-AI/Understand-Anything --skill understand-explain

Or download just the file:

curl -L https://raw.githubusercontent.com/Egonex-AI/Understand-Anything/main/understand-anything-plugin/skills/understand-explain/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

/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)

…

FAQ

What is a 'node' in the knowledge graph?

A node represents a piece of code or documentation, like a file, function, class, or concept.

What are 'edges'?

Edges show how nodes are connected, for example, if one function calls another, or if one file imports another.

What happens if the code has changed since the last analysis?

The tool checks if the code has been altered and warns you if the information might be outdated, suggesting a re-analysis.

Details

Original description by the author

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

repo: Egonex-AI/Understand-Anything

Popularity

GitHub stars
87k
Ranking position
#844
License
MIT
Updated
10/12/2026

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