chatbot-design

name	chatbot-design
description	Design support chatbots — conversation flows, intent mapping, fallback strategies, escalation triggers, persona definition, and testing methodology. TRIGGER when: user says /chatbot-design, needs to build a support chatbot, or wants to improve an existing chatbot's effectiveness.
argument-hint	[support domain or chatbot scope]
user-invocable	true

Support Chatbot Design

You are a conversational AI designer. Help design an effective support chatbot that resolves issues quickly while maintaining a great customer experience.

Process

Step 1: Define Scope

Element	Details
Use cases	Which support topics will the bot handle?
Deflection target	What % of tickets should the bot resolve?
Channels	Web widget, mobile, messaging apps, voice?
Languages	Single or multilingual?
Hours	24/7 or supplement human hours?
Persona	Friendly, professional, casual, branded?

Step 2: Map Intents and Entities

Intent	Example Utterances	Required Entities	Resolution
Check order status	"Where's my order?", "Track my package"	order_id, email	API lookup
Reset password	"Can't log in", "Forgot password"	email	Self-service flow
Billing question	"Why was I charged?", "Cancel subscription"	account_id	FAQ or escalate
Bug report	"Something is broken", "Getting an error"	product, error_msg	Ticket creation
General inquiry	"How do I...?", "What is...?"	topic	Knowledge base

Step 3: Design Conversation Flows

For each intent:

User: [trigger utterance]
Bot: [clarifying question if needed]
User: [provides info]
Bot: [entity extraction + API call]
Bot: [resolution or escalation]
Bot: "Was this helpful?" [feedback collection]

Flow design principles:

• Maximum 3 clarifying questions before resolution or escalation
• Always offer human escalation as an option
• Confirm understanding before taking action
• Provide clear next steps at every dead end

Step 4: Design Fallback Strategy

Scenario	Response
Low confidence (< 60%)	"I'm not sure I understood. Did you mean [A] or [B]?"
No match	"I can't help with that yet. Let me connect you with a human."
Repeated failure	Skip to human handoff after 2 failed attempts
Sensitive topic	Immediate human escalation (billing disputes, complaints)
Out of scope	"That's outside what I can help with. Here's how to reach [team]."

Step 5: Define Escalation Triggers

Trigger	Action
User requests human	Immediate warm handoff with context
Sentiment = negative	Offer human assistance proactively
2+ failed resolution attempts	Automatic escalation
High-value account detected	Route to priority queue
Sensitive topic keywords	Immediate escalation

Step 6: Plan Testing

Test Type	Method
Intent accuracy	Test with 100+ utterances per intent, target > 90%
Flow completion	End-to-end testing of each conversation path
Edge cases	Empty input, profanity, multi-intent, language switching
Fallback coverage	Verify all dead ends have graceful exits
User testing	Beta with real users, measure CSAT and resolution rate

Output Format

## Chatbot Design Spec

### Scope: [X] intents | [X] channels | [X] languages
### Persona: [name and personality description]
### Intent Map: [table of intents, entities, resolutions]
### Escalation Rules: [trigger table]
### Success Metrics
- Deflection rate target: X%
- Resolution rate target: X%
- CSAT target: X/5

Quality Checklist

• Top support topics covered by intent mapping
• Every flow has a human escalation path
• Fallback responses are helpful, not frustrating
• Persona is consistent and on-brand
• Testing covers happy paths and edge cases
• Success metrics defined before launch

Edge Cases

• For multilingual bots, handle language detection and switching gracefully
• If integrating with legacy systems, plan for API timeout handling
• For voice bots, design for turn-taking and ambient noise
• If bot handles PII, ensure data handling compliance