> ## Documentation Index
> Fetch the complete documentation index at: https://docs.graphify.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Ask better graph questions
> Use query, path, and explain for different kinds of codebase questions.
Start with a specific subsystem or concept, then narrow your investigation. A compact query is usually more useful to an assistant than the whole architecture report.
## Gather context with query
```bash theme={null}
graphify query "authentication and session storage" --budget 1500
```
`query` finds relevant starting nodes and traverses their relationships. Breadth-first traversal gathers a broader neighborhood. `--dfs` follows a deeper chain:
```bash theme={null}
graphify query "request validation" --dfs --budget 1500
```
## Inspect one concept with explain
Take a label or node ID from the query results:
```bash theme={null}
graphify explain "normalize_email"
```
Look at its source, community, and incoming and outgoing relationships. Inspect the source itself when a precise implementation detail matters.
## Trace a relationship with path
```bash theme={null}
graphify path "login" "normalize_email"
```
This uses the [tutorial’s example project](/guides/first-graph). In your project, replace the labels with real nodes. Stored direction is respected; add `--undirected` when you want connectivity rather than a directional path.
## Ask the assistant to preserve uncertainty
> Use Graphify to trace how a request reaches persistence. Show the path and source references. Flag inferred or ambiguous edges, and tell me if the graph is missing evidence.
The tool supplies context, and the assistant interprets it. Ask for evidence and avoid treating an absent path as proof that two systems are independent.