mcpbeat

Understand Chat

egonex-ai/understand-chat

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

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
77339
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Egonex-AI/Understand-Anything --skill understand-chat

The instruction itself

4 sections, as written by the author

/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 $UA_DIR. Run UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists in the current project root. If not, tell the user to run /understand first.
  • Check graph freshness before using graph-derived context:
  • Read project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
     GRAPH_COMMIT=$(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.
  • 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 id values of all matching nodes
  • 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
  • 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
  • If the query doesn't match any nodes, say so and suggest related terms from the graph

How to use it

Copy the folder

Take egonex-ai/understand-chat from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.