Run History

Run history provides a complete log of every agent execution — essential for debugging, auditing, and understanding agent behavior.

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What is a Run?

A run is a single execution of an agent in response to a customer message. Each run captures:

• The triggering message and conversation
• All steps the agent took
• Knowledge searched and retrieved
• Tools called and their results
• Response generated
• Classification applied

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Viewing Run History

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Run List View

The list shows:

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Filtering Runs

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By Date Range

• Last 24 hours
• Last 7 days
• Last 30 days
• Custom range

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By Status

• Success — Completed normally
• Escalated — Handed to human
• Error — Something went wrong

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By Category

Filter by assigned category.

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By Deployment

Filter by specific agent deployment.

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By Search

Search conversations by keyword.

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Run Details

Click any run to see complete details:

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Conversation

Full message thread between customer and agent:

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Execution Steps

Step-by-step breakdown of what happened:

1. Message received — Initial trigger
2. Guardrails checked — Safety evaluation
3. Knowledge searched — What was found
4. Runbook executed — Steps followed
5. Response generated — Final output
6. Classification applied — Category and attributes

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Knowledge Retrieved

See what knowledge was used:

• Articles retrieved
• Relevance scores
• Content highlighted

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Tool Calls

See what actions were taken:

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Classification

See how the conversation was tagged:

• Category: Billing, Technical, etc.
• Attributes: Priority, Product Area, etc.
• Resolution: Resolved or not

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Use Cases

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Debugging Issues

When something goes wrong:

1. Find the problematic run
2. Review execution steps
3. Identify where it failed
4. Fix the underlying issue

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Auditing Responses

Review what the agent said:

1. Filter by date range
2. Sample runs
3. Check response quality
4. Identify improvement areas

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Understanding Escalations

Why did the agent escalate?

1. Filter by status = Escalated
2. Review the conversation
3. Check which guardrail triggered
4. Decide if escalation was appropriate

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Training Improvement

Learn from real conversations:

1. Review successful runs
2. Identify patterns
3. Create knowledge from good examples
4. Update guidelines based on findings

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Volume Chart

See run volume over time:

• Identify busy periods
• Spot anomalies
• Correlate with events

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Exporting Runs

Export run data for analysis:

• CSV export
• Include conversation, metadata, classification
• Filter before export

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Next Steps