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Summary

This starter extends the customer-support case study into a connector-first local workflow: read Gmail through the Codex Gmail connector, classify customer issues with deterministic rules first, persist them in SQLite, and review or approve replies through a local dashboard.

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Status

starter Source code: case-studies/examples/customer-email-assist-starter

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Why It Exists

The earlier Customer Support Email Agent Starter shows the safer draft-only boundary. This follow-on starter keeps the same local-first posture, but adds the operational surfaces teams usually need next: Gmail connector import, local SQLite state, customer review queues, and a deterministic dashboard.

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Folder Structure

customer-email-assist-starter/
├── app/
│   ├── api/
│   ├── globals.css
│   ├── layout.tsx
│   └── page.tsx
├── index.mdx
├── package.json
├── README.md
├── scripts/
│   └── customer-email-assist.ts
├── skill/
│   └── SKILL.md
└── src/
    ├── components/
    ├── lib/
    └── test/

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Quick Start

Install dependencies and run the local dashboard: 
npm install
npm run setup-local
npm run dev
For the default connector-assisted low-token path, let Codex use the Gmail connector to produce a prepared inbound batch, then import that batch: 
tsx scripts/customer-email-assist.ts import-prepared-batch --input /tmp/prepared-inbound.json
Write intermediate batches to files instead of printing large JSON blobs to stdout: 
tsx scripts/customer-email-assist.ts prepare-draft-batch --out /tmp/draft-batch.json
An advanced direct Gmail OAuth adapter still exists for standalone local integrations, but it is not the default setup path: 
npm run sync:oauth
For the direct OAuth auto-send path, follow the starter README and use the dashboard Connect Gmail button after creating the Google OAuth client: 
case-studies/examples/customer-email-assist-starter/README.md
In connector-first mode, dashboard approval stores issues as approved_to_send for the Codex Gmail connector runner. If local OAuth is connected, the dashboard can execute the deterministic send path immediately after the undo countdown.

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Minimal-Token Boundary

This starter is designed to minimize model usage.
  • Hard logic handles Gmail connector import shaping, HTML stripping, signature trimming, quoted history removal, customer matching, SQLite persistence, analytics, and queue state.
  • The intended skill workflow reserves model usage for only two JSON-only surfaces:
    • understanding cleaned inbound customer messages
    • generating template-field JSON for reply drafts
  • The rendered reply text and HTML are produced locally from fixed templates, not from free-form model output.

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Included Sample Files

  • skill/SKILL.md: Codex workflow for the two model-backed steps plus the deterministic CLI commands
  • src/lib/email-processing.ts: HTML cleanup, quoted-history trimming, and heuristic classification helpers
  • src/lib/repository.ts: SQLite queries for issues, customers, analytics, and review actions
  • src/lib/sync.ts: deterministic inbound batch import, draft preparation, and draft rendering coordination
  • app/page.tsx: Next.js App Router dashboard with issues, analysis, customer review, and customer management
  • README.md: direct Gmail OAuth setup, dashboard connection flow, and optional runtime variables

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Constraints

  • Gmail authentication is expected to happen through the Codex Gmail connector in the normal workflow.
  • Direct Gmail OAuth exists as an advanced adapter for standalone local runs. Its required values are GOOGLE_CLIENT_ID and GOOGLE_CLIENT_SECRET; the dashboard connection flow stores the refresh token in local state.
  • Attachments and inline images are ignored in v1.
  • The dashboard is single-operator and local-machine oriented.
  • import-prepared-batch uses deterministic fallback understanding and drafting so the starter remains runnable without a live model call.
  • npm run setup-local resets the local SQLite database to an empty state.

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Verification

  • npm run lint
  • npm run test
  • npm run build

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Next Steps

  • Insert a real model-backed understand step between prepare-inbound-batch and persist-understanding.
  • Insert a model-backed draft-fields step between prepare-draft-batch and render-save-drafts.
  • Add a fixture-driven Gmail replay suite with sample labeled threads.