understand-chat

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• SKILL.md

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# /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:
     ```bash
     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
   - If the query doesn't match any nodes, say so and suggest related terms from the graph

From Egonex-AI/Understand-Anything, MIT.

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