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Use agent logs to inspect what happened after an agent run starts. In Fetch Hive, this is the main place to review run status, model usage, tool activity, cost, and trace timing outside the editor.

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Overview

Agent logs live under Logs in the agents section. The page centers on a table of runs. When you click a row, Fetch Hive opens a run detail sheet with summary metrics and trace data. This page covers logged runs, not the temporary test conversation in Chat. Use Chat in the editor to iterate on behavior, then use Logs to inspect runs after the fact.

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How do I open agent logs?

  1. Open Agents in the sidebar.
  2. Click Logs in the agents section menu.
Fetch Hive opens the agent logs table. On this page, the agents sidebar does not show the Categories group, and it does not add the Source filter pattern used in prompt and workflow logs.

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What’s tracked in the agent logs table?

The main logs table shows summary fields for each run, including:
  • Completed At
  • Name
  • Model
  • Tools
  • Status
  • Total Tokens
  • Total Cost
  • Duration
  • API Key
  • Collaborator
The Tools column shows the tool sources involved in the run. Depending on the run, this can include Google Search, GPT Search, xAI Web Search, X Search, Vector Search, SERP, or Image Generation. Total Tokens includes the parent agent response, sub-agent runs, and token-reporting image generation tool calls. In the run detail sheet, hover the token info icon to see the breakdown by parent agent, image generation, and sub-agents.

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How do I filter agent logs?

Use the date range control in the header to pick a custom range or an available preset. Presets include ranges such as Last 1 Day, Last 7 Days, Last 30 Days, and Last 90 Days, but longer ranges may require a plan with more log history. Use Provider, Model, and API keys to narrow the table to the runs you care about. Use User metadata to filter by a tracked metadata property. Choose a property key to find runs where that key exists, or add an exact value to match scalar values such as cus_123, enterprise, true, or 12. Click Clear filters when you want to reset the active filter state. Use Columns when you want to hide or restore table columns.

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How do I inspect an agent run?

  1. Click a row in the logs table.
  2. Review the run detail sheet that opens on the right.
The sheet header shows the request ID when it is available, or the run ID as a fallback. It also shows the run status, agent name, and started time. The summary strip below the header shows the run’s Provider / Model, Agent, Duration, Tokens, Credits, Cost, Tool Calls, Owner, and Charge Type. If the agent still exists and is not archived, the agent name in the summary strip links back to the editor.

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Traces

Use the trace waterfall on the left side of the run detail sheet to understand how the run progressed over time. When you select a span, the right side updates to show the details for that part of the run. Depending on the span, this can include:
  • model response data
  • request details
  • user metadata
  • metadata
  • tool input
  • tool response
  • token and cost details
When the selected span is linked to a tool completion, Fetch Hive shows the tool-specific panels for Response and Input. When it is linked to the main model completion, Fetch Hive shows the response and request sections for that completion instead. For sub-agent spans, Fetch Hive also shows the selected child agent run’s token and cost contribution. Nested sub-agents are included recursively in the run totals and remain visible in the trace waterfall. If a sub-agent fails, the span is kept with its input, safe failure response, child_request_id, metadata diagnostics, and any partial child trace/cost data that was written before failure. Late child runs are reconciled back into the parent trace by child_request_id after completion. For Claude agent completions, the request section can include Prompt Cache, which is the configured Anthropic prompt-cache TTL assigned to the run. Actual cache hit and write accounting remains in the cached-token usage fields. This is the main debugging view for agent runs. Start here when you need to understand whether the agent responded directly, reasoned first, called a tool, or slowed down on a specific step.

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Notes

  • Agent logs do not include the Source filter pattern used in prompt and workflow logs.
  • Fetch Hive tracks user metadata property names over time from agent invokes so the metadata filter can suggest keys your workspace has actually sent. See Invoke metadata for request examples.
  • This page does not expose a separate analytics or export view for agents.
  • Use Run with API when you want to invoke an agent from your own app, and use Testing with Chat when you want to iterate inside the editor.