Reading Sandbox Data
Understand the debug panels in the Agent Sandbox.
The Sandbox left panel gives you a live view of what Rian is doing internally. Here's how to read each tab.
Session tab
After sending a message, two data blocks appear:
Classification
| Field | What it means |
|---|---|
| Intent Class | Broad category (e.g. support, billing) |
| Intent | Specific intent detected (e.g. password_reset) |
| Scenario | The matched scenario within the flow |
| Confidence | 0.0–1.0; above 0.8 is good (green); below means Rian is uncertain |
| Intent locked | true when confidence exceeds 0.9; Rian commits to this intent |
Flow State
| Field | What it means |
|---|---|
| Active state | The flow currently running |
| Active step | The step within that flow |
| Attempts | How many times Rian tried this step |
| Outcome | resolved (handled); escalated (handed off); pending (still processing) |
Events tab
Four events are logged per simulation, each with a latency reading:
| Event | Description |
|---|---|
| classification | Intent detection; typically the fastest step |
| retrieval | Knowledge base search (cold tier) |
| llm call | The model call; shows model name and active step |
| transition | Flow state change; outcome is shown here |
High latency on retrieval means the cold knowledge base search is slow — consider adding more targeted articles so the hot/warm tiers are used instead.
Memory tab
Four tiers, each expandable to show key/value data:
| Tier | Badge | What it holds |
|---|---|---|
| Hot | in use | Active session context; current conversation state |
| Working | active | Short-term working memory for the current flow |
| Warm | cached | Recently accessed knowledge; fast retrieval |
| Cold | fetched | Full knowledge base search results |
Click any tier to expand it and see the actual data Rian is working with. The fetch latency for each tier is shown on the right.
What to look for
- Confidence below 0.8: knowledge gap; add or improve an article
- Outcome
escalatedunexpectedly: check escalation topic config - High cold fetch latency: knowledge base may be too large or poorly structured
- Empty hot/working memory: session may not have started correctly; try Reset Conversation