understand-chat

Original：🇺🇸 English

Translated

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

5installs

Added on2026-06-20

NPX Install

npx skill4agent add egonex-ai/understand-anything understand-chat

Answer questions about this codebase using the knowledge graph at

.understand-anything/knowledge-graph.json

.

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[]}

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