A rate limit on your API protects you from your users. A send limit on your email agent protects everyone else from your agent.

That asymmetry is why quota design deserves more thought than "set it high enough that we never hit it." An autonomous sender with an LLM in the loop has failure modes a human sender doesn't: retry storms that resend the same message, classification bugs that reply to mailer-daemons, a prompt-injected instruction that turns your agent into someone's spam cannon. The quota is the blast-radius control for all of them.

The defaults, and what they're for

On Nylas Agent Accounts (a beta feature), the cap is 200 messages per account per day on the free plan; paid plans have no daily cap by default. A stricter per-account quota can be set through a policy — policies bundle daily send quotas alongside storage, retention, and attachment limits, and attach to a workspace so every account in it inherits the same ceiling. Every limit on a policy is optional; omit one and it defaults to your plan's maximum.

That "stricter" direction is the point. The platform won't let you raise a limit above your plan — only constrain downward. So the design question becomes: what's the lowest quota each agent archetype can live with? A support triage agent answering inbound mail might legitimately need its full volume. A prototype you deployed Friday afternoon should probably be capped at 20. The docs recommend separate workspaces per agent archetype precisely so each group carries its own policy instead of one catch-all.

The limits nobody configures: bounce and complaint rates

Here's what surprises teams: the daily quota is rarely the binding constraint. Reputation thresholds are. The platform tracks each account's rolling bounce rate and complaint rate, and enforcement escalates as documented on the usage limits page:

Read that complaint row again: 0.1%. On a low-volume account, a handful of recipients clicking "Mark as spam" puts you under review. Only hard bounces — addresses that don't exist — count toward the bounce rate; soft bounces like a full mailbox or greylisting don't. The denominator in both rates is a recent representative send-volume window rather than a fixed time period, so the math stays meaningful whether you send a hundred messages a day or a million. Complaints are counted only against recipient domains that send complaint feedback to senders, which means your measured complaint rate understates reality — another reason not to ride the threshold.

Two more properties of this system change how you should monitor it. First, "under review" is silent: your sends keep succeeding and nothing in the API response tells you the account is being watched. The first hard signal your code receives is the pause itself. Second, pauses don't clear on a timer. A paused account stays paused until support clears it after you've shown what you fixed. That's a fundamentally different recovery contract than a 429 you can back off from — and it's why building your own telemetry (below) isn't optional.

What enforcement looks like in your code

Your send path needs to distinguish at least four responses:

• 429 Too Many Requests with "rate limit exceeded" — a per-account or per-domain rate limit. Back off and retry, or raise quotas via policy.
• 400 Bad Request mentioning a paused or suspended account — reputation enforcement. Retrying won't help; stop the campaign and investigate the bounce source.
• 403 Forbidden with "send blocked by abuse restriction" — an operations-applied abuse block, scoped to a sender, domain, organization, application, or grant. An application-level restriction affects every agent grant under that application, not just the misbehaving one.
• 403 from an outbound rule block — the send matched a block rule (your own do-not-contact list, say). No retry will deliver it; check GET /v3/grants/{grant_id}/rule-evaluations to see which rule matched.
• 400 Bad Request with "domain is not verified" — not an enforcement state at all, just an unfinished domain setup. Easy to misdiagnose as a block if your error handling only reads status codes.

Collapsing all of these into a generic retry loop is how a bad afternoon becomes a paused fleet.

Recovery paths, ranked by pain

When something does trip, the way out depends on which wall you hit. A 429 resolves itself: back off and retry, or raise the quota through policy. A reputation pause requires contacting support with details on the bounce or complaint source and the fix you applied — sending resumes only after Nylas clears it. An abuse restriction is the strictest of the three: there's no threshold you can stay under, because restrictions are applied when the operations team identifies abusive or out-of-policy use, not when a quota is exceeded. Include your application ID, the grant ID, and one example error response when you contact support so the team can locate the restriction. The one mercy: once cleared, sends start succeeding on the next attempt with no propagation delay.

Ordering your internal runbook around those three recovery contracts — self-service, support-with-evidence, support-with-explanation — is more useful than memorizing the status codes.

Build your own tripwire below the platform's

The platform's thresholds are the outer wall; you want an inner one that trips first. Four webhook triggers expose the exact events the rates are computed from — message.transactional.delivered, message.transactional.bounced, message.transactional.complaint, and message.transactional.rejected:

curl --request POST \
  --url "https://api.us.nylas.com/v3/webhooks" \
  --header "Authorization: Bearer $NYLAS_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "trigger_types": [
      "message.transactional.delivered",
      "message.transactional.bounced",
      "message.transactional.complaint",
      "message.transactional.rejected"
    ],
    "callback_url": "https://yourapp.example.com/webhooks/deliverability"
  }'

Compute your own rolling bounce and complaint rates from this stream and pause your own outbound logic at, say, half the platform thresholds. You'll see the problem in your telemetry before enforcement sees it in theirs — and a self-imposed pause is reversible the moment you fix the cause, while a platform pause needs a support conversation.

The standard hygiene list applies double for autonomous senders: validate addresses before sending, never resend to an address that hard-bounced, honor unsubscribes immediately, use double opt-in for any list that matters, and get DKIM, SPF, and DMARC right — authentication failures show up as bounces from servers refusing your mail outright.

Quota as a design discipline

The uncomfortable framing: if your agent can't articulate why it needs to send more than N messages a day, it shouldn't be able to. Per-archetype workspace policies make that enforceable rather than aspirational, and the thresholds above define the envelope you're designing inside either way.

Concrete next step: pull your agent's send volume for the last week, set a policy quota at roughly 2× its daily peak, and wire the four transactional triggers into a dashboard. When the quota trips unexpectedly, you'll be debugging a contained incident instead of a deliverability crisis.