understand-chat
Use when you need to ask questions about a codebase or understand code using a knowledge graph
- License 许可
- MIT
- 最近更新
- 2026-11-10
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- understand-chat
- description
- Use when you need to ask questions about a codebase or understand code using a knowledge graph
- argument-hint
- [ "query" ]
03 SKILL.md 正文
/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
- 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
-
Check that
.understand-anything/knowledge-graph.jsonexists in the current project root. If not, tell the user to run/understandfirst. -
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
- If the query doesn't match any nodes, say so and suggest related terms from the graph
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