Customer Support Email Agent Starter - Agent Systems Handbook by Prompthon

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Summary

This starter turns the customer-support case study into a small local workflow: read an inbound customer email, read a local support policy document, classify the case, and draft a safe reply for human review.

Status

starter Source code: case-studies/examples/customer-support-email-agent-starter

Why It Exists

Customer support is a practical local-agent shape because the useful context is often already nearby: an email export, a policy document, a refund rule, or an FAQ file. This starter keeps that boundary visible by requiring explicit local paths instead of pretending the agent knows the policy from memory.

Folder Structure

customer-support-email-agent-starter/
├── index.mdx
├── skill/
│   └── SKILL.md
└── src/
    ├── email_triage.py
    ├── policy_loader.py
    └── reply_guardrails.py

Quick Start

This is a starter, not a finished helpdesk integration. The code sketch uses only the Python standard library and focuses on the local-path boundary. Example:

from reply_guardrails import draft_policy_grounded_reply

result = draft_policy_grounded_reply(
    email_text="Subject: Refund request\nI received the wrong item.",
    policy_path="/Users/example/support/refund-policy.md",
)

print(result.reply_subject)
print(result.reply_body)
print(result.needs_human_review)

For a repo-level smoke check, run python3 scripts/verify_example_projects.py from the repository root.

Included Sample Files

skill/SKILL.md: skill instructions for checking customer email and drafting policy-grounded replies from a local document path
src/email_triage.py: lightweight classification and summary helpers
src/policy_loader.py: local policy loading and evidence extraction helpers
src/reply_guardrails.py: draft generation and human-review guardrails

Constraints

No mailbox, Gmail, CRM, or helpdesk adapter is implemented.
The starter reads local text-like policy files only.
Drafts are intended for human review, not automatic sending.
Classification is keyword-based and intentionally small.

Next Steps

Add a mailbox adapter that writes inbound messages to explicit local paths.
Add structured policy sections with stronger retrieval.
Add evaluation fixtures for refunds, billing, complaints, and escalation.
Add an audit artifact that records policy evidence and reviewer decision.

​Summary

​Status

​Why It Exists

​Related Lab Pages

​Folder Structure

​Quick Start

​Included Sample Files

​Constraints

​Next Steps