Agent Quality Loop
Woes agents are designed to answer from workspace-scoped evidence. The quality loop is the process of checking what the agent used, correcting weak answers, and improving the knowledge base so future replies get better.What To Review
Improvement Workflow
1
Review low-confidence conversations
Look for missing endpoints, unclear auth rules, stale examples, or ambiguous product language.
2
Fix the source
Update the external docs, upload better reference text, or add a repository with examples.
3
Rescan context
Re-ingest the source from Sources so the retrieval layer has the latest material.
4
Re-run learning
Run Context Learning when source coverage or agent routing changed materially.
5
Measure again
Use Analytics to watch answer rate, handoffs, feedback, and survey outcomes.
Good Agent Behavior
- Answer only from available workspace context.
- Ask a focused clarifying question when details are missing.
- Hand off to an operator when the question is account-specific, unsafe, or outside the knowledge base.
- Cite relevant source material when available.
- Avoid inventing endpoints, request fields, auth rules, schemas, limits, or production behavior.
