Reference
Runs
A run is one execution of an agent — every step it reasoned through, every tool it called, every action it proposed, with its outcome, token usage and cost. The run history and the run detail page are your forensic record of what each agent actually did.
What this area is for
The Runs list shows every agent execution in your organisation, live and historical. Each run is pinned to the immutable agent version that produced it, so a run always reflects the exact configuration in force at the time. Re-running or republishing later never rewrites the record.
Open any run to see its step timeline: the replayable narrative of everything the agent did, from model calls and tool calls through to proposed actions and approval waits. Alongside it sits a usage panel with token counts and cost, the run's input, and, once it finishes, the result.
The run history
The list opens newest-first and is fully filterable; every filter and the active column sort live in the URL, so a filtered view is shareable and survives a refresh. You can narrow by:
- Agent: runs from a single agent.
- Status: queued, running, awaiting approval, completed, failed or cancelled.
- Trigger: how the run started (for example manual or scheduled).
- Mode: live only, sandbox only, or both.
- Initiator: who started it. Runs with no initiator are shown as Scheduled.
- From / To: a date range.
You can sort by Started and Status; each row shows the agent, status with any outcome flag, trigger, who started it, total tokens, cost and when it began. A completed run whose proposed action later failed still reads completed, so the list surfaces a failed-action count to flag it. The list updates in real time as runs progress.
Inside a run
The detail page is built around the step timeline. Each step is one thing the agent did: a model call, a tool call, a proposed action, a simulated action, an approval wait, a retrieval, or a summary. A step expands to reveal its input and output payloads (loaded just after the page paints), its duration and token use, and any error. While a run is in flight the page streams the agent's reasoning live and refreshes as each step lands.
The side panel carries the run's Usage (input tokens, output tokens and cost), the model and provider used, the original Input, and, on completion, the Result summary. If the agent's version opted into retrieval, a Retrieved knowledge panel cites the source documents (name, id and similarity score) that grounded the run.
Actions, approvals and audit
Side-effecting tool calls never execute autonomously. Each becomes an action card on the run, gated by the approval centre. A card shows the tool, its risk level, the (redacted) payload and the approval outcome inline — who approved or rejected it, when, and any decision note. Decisions are never made from the run page: when an action is awaiting approval, the card links you through to the Approval Centre to decide it there.
When a run is paused on awaiting approval, a banner tells you how many decisions are pending and links straight to them. Every run and its steps are projected to the append-only audit log, so the record is permanent.
Cancel and re-run
Two actions are available from a run's header band, each behind its own permission:
-
Cancel run (requires
runs.cancel) is available while a run is still active (queued, running or awaiting approval). The run halts at its next safe checkpoint; tokens already consumed are still metered and the step record is retained. You are asked to confirm first. -
Re-run with same input (requires
runs.execute) is available once a run has finished. This starts a fresh manual run of the same agent with this run's input verbatim; it never mutates the original. The new run must pass every dispatch guard (your plan limits, an active agent, a published version), so it can be declined with a validation message.
Dry-run vs live
A sandbox dry-run lets an agent reason for real while every side-effecting and integration tool is simulated — nothing is sent, created or changed, no approval is requested, and the run does not count toward your plan limits or billing. Sandbox runs are badged in the list and carry a banner on their detail page.
Instead of executable action cards, a sandbox run shows would-be actions: exactly what the agent would have done live, including the redacted payload it would have used, surfaced as a forecast. Because they produce no real outcome, sandbox runs are never rated and never reach the approval gate. Use the Mode filter to separate live and sandbox history.