Rate Limits

Tier	Requests per minute	Burst
Standard	100	20
High-volume (on request)	500	50

Tier

Requests per minute

Burst

Standard

100

High-volume (on request)

500

Header	Description
`X-RateLimit-Limit`	Maximum requests allowed in the current window.
`X-RateLimit-Remaining`	Requests remaining in the current window.
`X-RateLimit-Reset`	Unix timestamp (seconds) when the window resets.

Header

Description

X-RateLimit-Limit

Maximum requests allowed in the current window.

X-RateLimit-Remaining

Requests remaining in the current window.

X-RateLimit-Reset

Unix timestamp (seconds) when the window resets.

Handling 429 responses

When you exceed the limit, the API returns 429 Too Many Requests with a Retry-After header:

HTTP/1.1 429 Too Many Requests
Retry-After: 15
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1748052600
Content-Type: application/json

{
  "detail": "Rate limit exceeded. Retry after 15 seconds."
}

Wait the number of seconds specified in Retry-After before retrying.

Best practices

Use exponential backoff

When you receive a 429, don’t retry immediately. Wait Retry-After seconds on the first retry, then double the wait on subsequent retries up to a maximum (e.g. 60 seconds).

import time
import requests

def request_with_backoff(url, headers, max_retries=3):
    for attempt in range(max_retries):
        response = requests.get(url, headers=headers)
        if response.status_code != 429:
            return response

        retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
        time.sleep(min(retry_after, 60))

    return response

Cache responses

Cache responses that don’t change frequently - session lists, template configs, org settings. Use Cache-Control or a local TTL to avoid unnecessary requests.

Batch operations

Instead of making one request per resource, use list endpoints with filters and pagination. A single GET /api/sessions?limit=100 replaces 100 individual GET /api/sessions/{id} calls.

Monitor your usage

Check X-RateLimit-Remaining in responses proactively. If you are consistently running close to the limit, consider requesting a higher tier or optimizing your request patterns.

API Reference

Patterns

Sessions

Deploy

Templates

Scheduled Agents

Agents

Groups

Deployments

Secrets

Context

Knowledge

Guardrails

Provider Keys

Activity

GitHub App

GitHub User Tokens

Linear

Slack

WebSockets

Default limits

Rate limit headers

Handling 429 responses

Best practices

​Default limits

​Rate limit headers

​Handling 429 responses

​Best practices

Default limits

Rate limit headers

Handling 429 responses

Best practices