understand-chat

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Answer questions about this codebase using the knowledge graph at

.understand-anything/knowledge-graph.json

借助

.understand-anything/knowledge-graph.json

中的知识图谱，回答关于此代码库的问题。

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?}
- Node types: file, function, class, module, concept
- IDs:
```
file:path
```
  ,
```
func:path:name
```
  ,
```
class:path:name
```
```
edges[]
```
— each has {source, target, type, direction, weight}
- Key types: imports, contains, calls, depends_on
```
layers[]
```
— each has {id, name, description, nodeIds[]}
```
tour[]
```
— each has {order, title, description, nodeIds[]}

知识图谱JSON的结构如下：

```
project
```
— {name, description, languages, frameworks, analyzedAt, gitCommitHash}
```
nodes[]
```
— 每个节点包含{id, type, name, filePath, summary, tags[], complexity, languageNotes?}
- 节点类型：file、function、class、module、concept
- ID格式：
```
file:path
```
  、
```
func:path:name
```
  、
```
class:path:name
```
```
edges[]
```
— 每条边包含{source, target, type, direction, weight}
- 主要边类型：imports、contains、calls、depends_on
```
layers[]
```
— 每个层级包含{id, name, description, nodeIds[]}
```
tour[]
```
— 每个导览项包含{order, title, description, nodeIds[]}

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

Check that
```
.understand-anything/knowledge-graph.json
```
exists in the current project root. If not, tell the user to run
```
/understand
```
first.
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

检查当前项目根目录下是否存在
```
.understand-anything/knowledge-graph.json
```
。如果不存在，告知用户先运行
```
/understand
```
命令。
仅读取项目元数据——使用Grep或限制行数的读取方式，从文件顶部提取
```
"project"
```
部分的内容作为上下文（包括名称、描述、使用的语言和框架）。
搜索相关节点——使用Grep在知识图谱文件中搜索用户查询的关键词："$ARGUMENTS"
- 搜索
```
"name"
```
  字段：在图谱文件中使用
```
grep -i "query_keyword"
```
  命令
- 搜索
```
"summary"
```
  字段以找到语义匹配的内容
- 搜索
```
"tags"
```
  数组以找到主题匹配的内容
- 记录所有匹配节点的
```
id
```
  值
查找关联的边——对于每个匹配的节点ID，在
```
edges
```
部分中用Grep搜索该ID，以找到：
- 它导入或依赖的内容（下游）
- 调用或导入它的内容（上游）
- 这将为你提供查询内容周围的1跳子图谱
读取层级上下文——使用Grep搜索
```
"layers"
```
部分，以了解匹配节点所属的架构层级。
仅使用相关子图谱回答查询：
- 引用图谱中的具体文件、函数和关系
- 说明哪些层级相关以及原因
- 表述简洁但全面——将概念与实际代码位置关联起来
- 如果查询未匹配到任何节点，告知用户这一情况，并建议使用图谱中的相关术语