Agent Blueprint: Support Ticket Classification and Draft Reply
A support agent blueprint for classifying tickets, retrieving approved context, and drafting safer replies before human review.
Use cases
Customer Support, Operations & Workflow
Platforms
Claude, GPT, Model-Agnostic
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The resource
Copy and adapt. Do not paste blind.
Workflow:
1. Receive incoming ticket.
2. Classify issue type, priority, and likely queue.
3. Retrieve relevant policy or knowledge-base material.
4. Check whether the retrieved material is sufficient to answer safely.
5. Draft reply using only approved context.
6. Flag confidence, missing information, and escalation status.
7. Send to human review or auto-send only for low-risk categories with explicit approval rules.
Guardrails:
- Never auto-send billing, security, compliance, or account-access decisions without explicit approval rules.
- Never invent policy.
- Escalate angry, ambiguous, or high-risk tickets quickly.
- If retrieval is weak, ask for clarification or escalate instead of bluffing.When to Use This
Use this when support volume is high enough that queueing and first-draft creation need help, but answer quality and escalation still matter.
It is useful for SaaS support teams, service teams, and founders handling support with a lean operation.
Why It Works
The blueprint separates classification, retrieval, and drafting. That makes the workflow easier to debug and much safer than a single-step "read ticket and reply" system.
The key guardrail is low-risk-only auto-send. Most support damage happens when a workflow sounds helpful in situations where it should have escalated.
How to Customise
Customise the queue types, escalation rules, and send or no-send thresholds for your business.
If you already use macros or standard response patterns, make them available during retrieval so the draft stays closer to your actual support practice.
Limitations
This improves operational speed, but it does not replace a strong support knowledge base or clear policy.
If the support rules are messy, the automation will surface that mess rather than fix it.
Model Notes
Claude is strong for tone and escalation sensitivity.
GPT works well when the classification and routing outputs need to be extremely structured. Model-agnostic overall if policy context is clean.
Related Resources
Browse AgentsSkill: Customer Support Triage
A reusable support triage skill for classifying requests, assessing urgency, gathering missing context, and preparing a safe first reply.
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Agent Blueprint: Internal Knowledge Base Answering Workflow
A knowledge-answering blueprint for retrieving internal docs, drafting grounded answers, and escalating low-confidence responses instead of bluffing.
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Skill: QA Reviewer for AI Drafts
A review skill for catching weak claims, structural drift, tone problems, and hidden assumptions in AI-generated drafts before they go live.
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