A signal is a detector. It watches agent runs and fires when findings match a pattern described in plain English: “the agent retries a failed charge with no backoff,” “the assistant goes off-topic.” These live under Signals in the dashboard. A signal is a learned classifier, not a hand-written rule. Bento trains it on your own runs through the Deep Search loop, and once trained it fires in real time on new runs and backfills history. Each firing is an event, and Bento groups similar events into clusters. Every signal carries a source and a status:Documentation Index
Fetch the complete documentation index at: https://docs.bentolabs.ai/llms.txt
Use this file to discover all available pages before exploring further.
| Field | Values |
|---|---|
| Source | auto, classifier, instrumented, monitored, self_diagnostic, tool_error, metric, deep_search |
| Status | initializing (training), active (live), paused, archived, failed |
Commands
| Command | What it does |
|---|---|
signals list | List signals. Filter by source, status, or group. |
signals get <signal-id> | Open one signal with its full config and event_count. |
signals list-events <signal-id> | The firings, what the signal matched on. |
signals list-clusters <signal-id> | Groupings of similar events for that signal. |
signals create | Register a signal record by hand. |
signals update <signal-id> | Edit a signal’s name, prompt, or config. |
signals delete <signal-id> | Archive a signal (soft delete). |
Read what’s firing
List the signals:--status takes initializing, active, paused, archived, or failed:
--source takes any of the source values above:
event_count:
--start-time:
Create and edit
The Deep Search loop trains a working detector. To register a record directly,signals create takes a body where name is required and prompt describes the pattern in plain English. A hand-created record lands in initializing and waits for its training step; it doesn’t train a classifier on its own.
signals delete is a soft delete. The record stays, the status flips to archived, and it stops firing:
See also
Deep Search
The labeling loop that trains a signal from your own runs.
Clusters
Groupings of similar findings and signal events.
Issues
The tracked problems a signal helps surface.