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
Ready-to-paste message
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-chatOr 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.mdTechnical 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
- Use Grep to search within the JSON for relevant entries BEFORE reading the full file
- Only read sections you need — don't dump the entire graph into context
- Node names and summaries are the most useful fields for understanding
- Edges tell you how components connect — follow imports and calls for dependency chains
Instructions
Resolve the data directory
$UA_DIR. RunUA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua)— this is the legacy.understand-anything/when it already exists, otherwise the new.ua/. Check that$UA_DIR/knowledge-graph.jsonexists in the current project root. If not, tell the user to run/understandfirst.Check graph freshness before using graph-derived context:
- Read
project.gitCommitHashfrom the graph metadata asGRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it withgit rev-parse HEADand inspect project-scoped committed and working-tree changes from the project root:GRAPH_COMMIT=$(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
/understandto refresh the graph. - Run the commit diff only when
GRAPH_COMMIT_RAWresolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
- Read
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).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
idvalues of all matching nodes
- Search
Find connected edges — for each matched node ID, Grep for that ID in the
edgessection 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
Read layer context — Grep for
"layers"to understand which architectural layers the matched nodes belong to.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
Popularity
- GitHub stars
- 87k
- Ranking position
- #840
- License
- MIT
- Updated
- 10/12/2026
Comments
- …
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