git:20260708.0bae36e to git:20260710.e82fe96

49 added, 36 removed. Audit A to A.

- ---
- name: understand-chat
- description: Use when you need to ask questions about a codebase or understand code using a knowledge graph
- argument-hint: "[query]"
- ---
-
- # /understand-chat
-
- Answer questions about this codebase using the knowledge graph at `.understand-anything/knowledge-graph.json`.
-
- ## 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. Check that `.understand-anything/knowledge-graph.json` exists in the current project root. If not, tell the user to run `/understand` first.
-
- 2. **Check graph freshness** — read `project.gitCommitHash` from the graph metadata and run `git rev-parse HEAD` in the project root. If both values exist and differ, warn the user before answering that the knowledge graph may be stale and newer code may be missing from the answer. Suggest: Run `/understand` to refresh the graph. If git metadata is missing or unavailable, continue with a brief best-effort warning instead of blocking.
+ ---
+ name: understand-chat
+ description: Use when you need to ask questions about a codebase or understand code using a knowledge graph
+ argument-hint: "[query]"
+ ---
+
+ # /understand-chat
+
+ Answer questions about this codebase using the knowledge graph at `.understand-anything/knowledge-graph.json`.
+
+ ## 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. Check that `.understand-anything/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 "$GRAPH_COMMIT" HEAD -- .
+ git diff --cached --name-only -- .
+ git diff --name-only -- .
+ git ls-files --others --exclude-standard -- .
+ ```
+ - The `-- .` pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty.
+ - Ignore `.understand-anything/` paths in every command's output because they are generated graph artifacts, not project source drift.
+ - If the committed diff or any working-tree command reports project files, warn before answering that graph-derived context may omit those changes. Suggest: Run `/understand` to refresh the graph.
+ - Run the commit diff only when `GRAPH_COMMIT_RAW` resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
3. **Read project metadata only** — use Grep or Read with a line limit to extract just the `"project"` section from the top of the file for context (name, description, languages, frameworks).
4. **Search for relevant nodes** — use Grep to search the knowledge graph file for the user's query keywords: "$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