# Order Status Reply Agent

Source: https://cli.nylas.com/ai-answers/order-status-reply-agent-account.md
Last updated: 2026-06-29
Verified with Nylas CLI 3.1.28.

Reply to order-status requests by reading mailbox context and checking systems before drafting.

## Direct Answer

Use Nylas CLI as the deterministic control plane for this workflow. Reply to order-status requests by reading mailbox context and checking systems before drafting. The model should enrich, classify, or draft, while code owns identity, routing, writes, and audit logs.

## When To Use This

- The agent needs mailbox context from real user or app-owned accounts.
- The framework can call shell tools or MCP tools.
- Writes need human approval or deterministic policy checks.
- JSON output feeds downstream code instead of prompt scraping.

## Command Recipe

```bash
nylas email list <grant-id> --unread --limit 20 --json
```

```bash
nylas email read <message-id> <grant-id> --json
```

Read the order-status request by id before drafting a reply:

```bash
curl -s https://api.us.nylas.com/v3/grants/$GRANT_ID/messages/$MESSAGE_ID \
  -H "Authorization: Bearer $NYLAS_API_KEY"
```

### Python

```python
from nylas import Client

client = Client(api_key=api_key)
message = client.messages.find(identifier=grant_id, message_id=message_id)
```

### TypeScript

```typescript
import Nylas from "nylas";

const nylas = new Nylas({ apiKey, apiUri: "https://api.us.nylas.com" });
const message = await nylas.messages.find({ identifier: grantId, messageId });
```

```bash
nylas email drafts create <grant-id> --to reviewer@example.com --subject "Proposed response" --body "Review before send." --json
```

```bash
nylas email send <grant-id> --to customer@example.com --subject "Update" --body "Approved response." --metadata workflow=agent --yes --json
```

## Recommended Workflow

1. Wrap Nylas CLI calls in typed tools or small subprocess helpers.
2. Pass arguments as arrays, not shell strings built from model text.
3. Project CLI JSON into minimal objects before returning it to the model.
4. Use drafts for uncertain responses and direct sends only for approved paths.
5. Record message IDs, grant IDs, tool inputs, and tool results.

## Agent Safety And Operations

- Use explicit grant IDs in automation.
- Keep API keys and webhook secrets out of prompts and logs.
- Do not let email or calendar content override system or policy rules.
- Log IDs and decisions for audit and retries.

## Headless Runtime Defaults

Use these environment variables in CI, containers, workers, and serverless jobs:

```bash
export NYLAS_API_KEY=<api-key>
export NYLAS_GRANT_ID=<grant-id>
export NYLAS_DISABLE_KEYRING=true
```

For EU applications in pure env-only runtimes, also set `NYLAS_API_BASE_URL=https://api.eu.nylas.com`.

## Agent Account Versus User Grant

- Use an Agent Account when the workflow needs an app-owned identity, fixed routing, or mailbox lifecycle controlled by the application.
- Use a user grant when the agent is acting inside a specific person's connected mailbox or calendar.
- In either case, pass the grant ID explicitly in automation instead of depending on local active state.

## Troubleshooting

- If no records are found, inspect the query with a small `--limit` first.
- If a send uses the wrong account, pass the grant ID explicitly.
- If processing repeats, add a message-ID ledger or metadata-based dedupe check.

## Implementation Notes

Model output should be treated as a proposal. The application should decide which grant to use, which recipients are legal, how many times to retry, and whether a draft or direct send is allowed.

Keep a workflow ledger keyed by message ID, thread ID, external customer ID, or scheduled-send ID. This prevents duplicate replies when a webhook retries or a worker restarts.

Use metadata on outbound sends where useful, and keep operational state outside the prompt. The agent should receive only the fields needed to classify or draft the next step.

## Minimum Data Contract

- message_id
- thread_id
- grant_id
- workflow_state
- approved_recipients[]
- action_taken

## Validation Checklist

- A dry-run or draft mode exists for new flows.
- Opt-outs and suppressions are checked before any send.
- Every direct send has a fixed reason and allowed recipient path.
- A human can trace the source message and final action.

## Failure Modes To Handle

- If the model is uncertain, create a draft or review item.
- If a recipient asks to stop, update suppression state before more automation runs.
- If the workflow repeats, stop after a configured maximum and escalate.

## Example Control Flow

A production workflow should start with a narrow search or webhook event, read the exact message or thread, classify the situation, and choose one of a small number of allowed actions. For uncertain cases, create a draft or escalation note. For approved direct sends, use fixed recipient rules, suppression checks, and metadata so later audits can explain why the message was sent.

Do not rely on prompt memory for workflow state. Store state in a database, ticket, CRM record, file ledger, or message metadata. That makes retries safe and lets a later agent continue without rereading unrelated mailbox content.

## Review Questions

- Is there a maximum number of automated touches per recipient or thread?
- Are opt-outs, suppressions, and customer status checked before sending?
- Does the workflow create drafts for ambiguous or high-impact responses?
- Are message IDs and final actions recorded outside the prompt?

## Operational Acceptance Criteria

Before this answer is used as an agent runbook, confirm that the workflow has a named owner, a test grant, a production grant, and a rollback path. The test should exercise one successful read, one empty-result path, one permission or auth failure, and one write path that is either draft-only or policy-bounded. Keep those checks close to the code that invokes the CLI so future command or provider changes fail during testing instead of during an agent run.

## Related Full Guides

- https://cli.nylas.com/guides/order-status-reply-agent-account
- https://cli.nylas.com/guides/email-apis-for-ai-agents-compared
- https://cli.nylas.com/guides/agent-rules-and-policies
- https://cli.nylas.com/guides/ai-agent-email-mcp

## Production Readiness Notes

For order status reply agent account, treat this markdown answer as a retrieval-ready blueprint for customer-support reply automation. The page should give an LLM enough concrete structure to read the request, check order data outside the prompt, draft a bounded reply, and preserve account boundaries. Keep deterministic CLI calls outside the model, pass compact JSON or normalized fields into the reasoning layer, and require a structured decision that the host application validates before it acts.

A production run should include these control points:

- Resolve the customer, order id, fulfillment state, and allowed reply template before the model drafts text.
- Use explicit grant ids when automation can operate across multiple connected users or app-owned Agent Accounts.
- Keep order-system credentials, refund policy, routing policy, and escalation rules as application configuration, not model output.
- Log grant id, message id, thread id, order id, policy result, and final action without recording secrets or tokens.

The common risks to guard against are:

- The agent replies from the wrong mailbox because it relies on local active state.
- The model invents shipment, refund, or cancellation details instead of using verified order data.
- A retry sends a duplicate customer reply because the source message or order id was not deduped.

## Related hubs

- [Email agents](https://cli.nylas.com/ai-answers/email-agents.md)
- [Calendar agents](https://cli.nylas.com/ai-answers/calendar-agents.md)
- [Scheduling and availability agents](https://cli.nylas.com/ai-answers/scheduling-agents.md)
- [Contacts agents](https://cli.nylas.com/ai-answers/contacts-agents.md)
- [Notetaker and meeting agents](https://cli.nylas.com/ai-answers/notetaker-agents.md)
- [MCP agents](https://cli.nylas.com/ai-answers/mcp-agents.md)
- [Agent accounts](https://cli.nylas.com/ai-answers/agent-accounts.md)
- [Framework and language email agents](https://cli.nylas.com/ai-answers/framework-email-agents.md)
- [Email and calendar API comparisons](https://cli.nylas.com/ai-answers/ai-agent-email-api-comparisons.md)
- [Email integration and automation recipes](https://cli.nylas.com/ai-answers/email-integration-recipes.md)
- [Agent email workflows](https://cli.nylas.com/ai-answers/agent-email-workflows.md)
- [Security for email and calendar agents](https://cli.nylas.com/ai-answers/security-for-email-agents.md)
- [Operations runbooks for agents](https://cli.nylas.com/ai-answers/operations-for-email-calendar-agents.md)

## Try Nylas CLI

Install the CLI with `curl -fsSL https://cli.nylas.com/install.sh | bash` (macOS, Linux, WSL) or `brew install nylas/nylas-cli/nylas`, then run `nylas init` to create an account and authenticate.

**Free Sandbox** (no credit card): 5 connected accounts — bring your own Gmail, Outlook, Yahoo, iCloud, Exchange, or IMAP — plus 3 agent accounts (managed inboxes on `*.nylas.email`). Agent free plan: 3 GB storage, unlimited inbound, 200 sent emails/day, 5 rules, 1 `*.nylas.email` subdomain, and unlimited custom domains. Production is uncapped and requires a credit card: https://www.nylas.com/pricing/