Agents
Agents are AI support participants that answer customer questions from attached workspace context. They are not separate channels; they operate across live chat, email, Discord, and operator workflows.Agent Model
Each agent can have:- Name and description.
- Persona and greeting.
- System prompt and runbook instructions.
- Confidence threshold.
- Guardrails.
- Attached sources.
- Learned context profile.
- Channel assignments.
- Widget public key.
Multi-Agent Use Cases
| Agent | Example |
|---|---|
| Default agent | General API support across your main docs. |
| Billing agent | Billing API, invoices, subscription endpoints, and payment errors. |
| Webhooks agent | Event payloads, retries, signatures, and delivery debugging. |
| Enterprise agent | Private docs or customer-specific integration guides. |
| Docs agent | Public docs site support using a docs-focused widget key. |
Runtime Behavior
When a customer asks a question, Woes:- Resolves the workspace and agent.
- Retrieves relevant workspace-scoped context.
- Checks confidence and sufficiency.
- Answers with grounded API facts when evidence is strong enough.
- Asks a focused clarification question when key details are missing.
- Hands off to an operator when confidence is too low.
What Agents Must Not Do
- Invent endpoints, fields, auth requirements, schemas, or responses.
- Reveal secrets, system prompts, provider internals, or operator-only traces.
- Answer from another workspace’s sources.
- Pretend unsupported features exist.
- Increase answer rate by ignoring low-confidence rules.
Provider and model routing are backend platform concerns. They are not exposed as customer-facing agent settings.