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understand-chat

Has your agent understand and explain codebases. It's useful for analyzing existing code or answering questions about how a program works.

What it does

This tool helps you understand a code project. It uses a knowledge map to answer questions about files, functions, and how everything is connected.

When to use it

  • ✓When you don't understand a specific piece of code.
  • ✓To see how different parts of the project relate to each other.
  • ✓To get a quick summary of what a file or function does.

Example of what to ask your AI

“Explain the 'calculate_total' function in the 'utils.py' 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-chat/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-chat/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool consults a special file (the knowledge map) that describes the code. It looks for information related to your question and shows how code parts are linked.

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-chat

Or download just the file:

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

Original text by the author, straight from GitHub.

/understand-chat

Answer questions about this codebase using the knowledge graph in the project's data directory (.ua/knowledge-graph.json, or the legacy .understand-anything/knowledge-graph.json when that directory is present).

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 in the current project root. 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 answering 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. Read project metadata only — use Grep or Read with a line limit to extract just the "project" section from the top of the file for context (name, description, languages, frameworks).

  4. Search for relevant nodes — use Grep to search the knowledge graph file for the user's query keywords: "$ARGUMENTS"

    • Search "name" fields: grep -i "query_keyword" in the graph file
    • Search "summary" fields for semantic matches
    • Search "tags" arrays for topic matches
    • Note the id values of all matching nodes
  5. Find connected edges — for each matched node ID, Grep for that ID in the edges section to find:

    • What it imports or depends on (downstream)
    • What calls or imports it (upstream)
    • This gives you the 1-hop subgraph around the query
  6. Read layer context — Grep for "layers" to understand which architectural layers the matched nodes belong to.

  7. Answer the query using only the relevant subgraph:

    • Reference specific files, functions, and relationships from the graph
    • Explain which layer(s) are relevant and why
    • Be concise but thorough — link concepts to actual code locations

…

FAQ

What is a 'knowledge map'?

It's a file containing organized information about the code, like file names, functions, what they do, and how they link together.

What if the knowledge map is outdated?

The tool might warn you that the code has changed since the map was created and suggest you update it.

How does the tool find information?

It searches for keywords from your question in the names, descriptions, and tags within the knowledge map and follows the connections between code parts.

Details

Original description by the author

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

repo: Egonex-AI/Understand-Anything

Popularity

GitHub stars
87k
Ranking position
#840
License
MIT
Updated
10/12/2026

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