Agents are the AI assistants at the heart of Duckie. Each agent is a configured AI that handles customer conversations according to your instructions, resources, and deployment settings.Documentation Index
Fetch the complete documentation index at: https://docs.duckie.ai/llms.txt
Use this file to discover all available pages before exploring further.
What is an Agent?
An agent is a complete AI assistant configured with:- Start mode — Autonomous, workflow, or runbook behavior
- Instructions — The agent’s role, scope, and decision rules
- Knowledge — Sources it can search for information
- Guidelines — Rules for communication style and tone
- Guardrails — Safety constraints and escalation rules
- Tools — Actions it can perform (respond, search, escalate, call APIs)
Agent Capabilities
Agents can:| Capability | Description |
|---|---|
| Respond to customers | Generate and send replies across Zendesk, Slack, Intercom, and more |
| Search knowledge | Find relevant information from your connected documentation |
| Follow procedures | Execute runbooks or workflows you define |
| Take actions | Create tickets, update records, send messages, call APIs |
| Escalate | Hand off to humans when guardrails trigger |
| Classify | Tag conversations with categories and attributes |
Start Modes
Every agent has a start mode:| Mode | Best for | How it works |
|---|---|---|
| Autonomous | Open-ended support where the agent needs to choose what to research or do | Starts from agent instructions and decides which runbooks, workflows, knowledge, and tools to use |
| Workflow | Deterministic processes | Starts at a selected workflow and follows its nodes and branches |
| Runbook | One flexible procedure | Starts from a selected runbook and follows its instructions |
Autonomous Agents
Learn how to configure agents that decide which resources and tools to use at run time.
Agent Configuration
Knowledge Sources
Control what information the agent can access:- Leave knowledge tags empty to allow all connected and custom knowledge
- Use knowledge tags to narrow what’s searchable
- Mix connected sources with custom articles
Guidelines
Shape how the agent communicates:- Tone and voice (friendly, professional, casual)
- Response format and length
- Brand terminology and phrases
- Domain-specific instructions
Guardrails
Define safety boundaries:- Escalation rules — When to hand off to humans
- Restrictions — What the agent cannot do or say
Classification
Configure how conversations are tagged:- Categories (Billing, Technical Support, etc.)
- Custom attributes (Priority, Product Area, etc.)
Multiple Agents
You can create multiple agents for different purposes:| Strategy | Example |
|---|---|
| By team | Billing Agent, Technical Support Agent, Sales Agent |
| By channel | Slack Agent (casual), Zendesk Agent (formal) |
| By customer | Enterprise Agent (high-touch), Self-serve Agent |
| By product | Product A Agent, Product B Agent |
Agent vs Runbook vs Workflow
| Concept | What It Is | Example |
|---|---|---|
| Agent | The complete AI assistant with instructions, resources, tools, and deployment settings | ”Support Agent” |
| Autonomous mode | A start mode where the agent decides which resources and tools to use | ”Research the issue, read relevant runbooks, call tools as needed, then respond” |
| Runbook | Flexible instructions the agent follows | ”When a customer asks about refunds, verify their order, check eligibility, process or explain policy” |
| Workflow | Visual process with explicit steps and branches | Start → Check Order → Decision: Eligible? → Yes: Process Refund / No: Explain Policy |
Next Steps
Create an Agent
Step-by-step guide to your first agent
Agent Configuration
Deep dive into all settings
Autonomous Agents
Configure flexible agents for open-ended conversations
Workflows
Learn about visual workflows
Runbooks
Learn about flexible, AI-driven runbooks