# Log History

Use log history in Fetch Hive when you want to review individual prompt, workflow, or agent runs and inspect what happened during a request.

## Overview

Fetch Hive gives you separate log views for prompts, workflows, and agents. Each view starts with a table of runs, then lets you open a detail sheet for a deeper trace and run-level inspection.

These log views are for resource-level investigation. If you want to start from a tracked end user and then open their runs, see [Filtering and drilling](https://docs.fetchhive.com/user-tracking/filtering-and-drilling).

## How do I open logs for prompts, workflows, or agents? <a href="#open-logs" id="open-logs"></a>

Open one of these sections in the main sidebar:

* **Prompts**
* **Workflows**
* **Agents**

Then click **Logs** in the secondary navigation.

Fetch Hive opens the log table for that resource type.

Prompt and workflow logs also expose a **Source** section in the secondary navigation so you can switch between **All Sources**, **Dashboard**, and **Live**.

## How do I filter logs? <a href="#filter-logs" id="filter-logs"></a>

All three log pages use the date-range control in the header, pagination, and column visibility controls in the table.

Each log page also has its own filter set:

* **Prompts** logs support **Provider**, **Model**, **API keys**, and **Prompt**
* **Workflows** logs support **API keys**, **Workflow**, and **Trigger**
* **Agents** logs support **Provider**, **Model**, and **API keys**

The **Trigger** filter on workflow logs lets you switch between **All**, **Async**, and **Sync** runs.

Some filter pickers also include an inline search field so you can quickly find a prompt or workflow in the list.

Use **Clear filters** to reset the active filter set for the current log view.

## What's tracked

The log tables surface the main run fields you use during debugging and monitoring. Depending on the resource type, Fetch Hive shows combinations of:

* Completion or run time
* Resource name
* Provider or model details
* Tool usage
* Status
* Total cost
* Total tokens
* Duration
* API key
* Collaborator

Prompt logs include **Total Tokens** and **Total Cost** in the main table.

Agent logs also include **Total Tokens** and **Total Cost** in the main table, along with a **Tools** column.

Workflow logs focus on **Tools**, **Total Cost**, **Duration**, **API Key**, and run status.

## How do I read a run detail sheet? <a href="#read-run-detail-sheet" id="read-run-detail-sheet"></a>

Click a row in the logs table to open the matching detail sheet.

The sheet starts with a header that shows the request or run ID, the current status, and any live deployment badge when that run came from a deployment.

Below that, Fetch Hive shows a summary strip with the most important run-level details, such as duration, cost, tokens, tool counts, owner, or charge type, depending on the run type.

On the right side of the sheet, Fetch Hive shows the detailed content for the selected run or span. This can include response content, request details, inputs, metadata, and output sections.

## Traces <a href="#traces" id="traces"></a>

When a run has a trace, Fetch Hive shows a waterfall panel on the left side of the detail sheet.

Use this panel to move through the run step by step. Selecting a span updates the detail panel so you can inspect that span's timing and payload details.

Span details can include:

* Duration
* Percent of total run time
* Start and completion timestamps
* API key
* User
* Metadata
* Output

For prompt, workflow, and agent runs, this trace view is the fastest way to understand which part of a request took time, failed, or produced a specific output.

## Notes

* Prompt and workflow logs support **Source** switching between **Dashboard** and **Live**, but agent logs do not expose that navigation.
* Workflow logs refresh running rows as status changes, and a running workflow row does not open the detail sheet until the run is no longer running.
* The trace waterfall appears when the run has trace data available.
* You can also open these same detail sheets from the **Users** section after drilling into a tracked end user.

See also: [Credit Usage](https://docs.fetchhive.com/monitoring/credit-usage).