Anth Rate Limits

What it does

When your agent uses it

• Handling 429 errors
• Optimizing request throughput
• Managing RPM/TPM limits across usage tiers
• With phrases like anthropic rate limit

Example prompts

• “anthropic rate limit”
• “claude 429”
• “anthropic throttling”
• “/anth-rate-limits”

Requirements

• Python 3
• Compatibility (from SKILL.md): Designed for Claude Code
• Pre-approved tools (allowed-tools): Read, Write, Edit

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Read the response headers after each permitted call and update a shared limiter using the provider's remaining/reset values. Reserve…
2. 2Honor retry-after when present, apply jitter and a maximum delay, and stop after a bounded number of attempts. Never let every worker…
3. 3Coordinate RPM, input-token, and output-token budgets across instances. Queue or batch offline work and apply backpressure when the shared…
4. 4Canary limiter changes with synthetic traffic and compare 429 rate, latency, queue age, token totals, and side_effects=0. Roll back the…
5. 5Expire queued test items and temporary counters according to the retention policy; retain a redacted receipt for the decision.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python and typescript).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • platform.claude.com
  • console.anthropic.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Designed for Claude Code

  From compatibility in the SKILL.md frontmatter.

Context cost

Anth Rate Limits loads about 1.9k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 453 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~82

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 453 words, ~1,879 tokens.

name

anth-rate-limits

description

Implement Anthropic Claude API rate limiting, backoff, and quota management. Use when handling 429 errors, optimizing request throughput, or managing RPM/TPM limits across usage tiers. Trigger with phrases like "anthropic rate limit", "claude 429", "anthropic throttling", "claude retry", "anthropic backoff".

allowed-tools

Read, Write, Edit

compatibility

Designed for Claude Code

version

1.7.0

license

MIT

author

Jeremy Longshore <jeremy@intentsolutions.io>

tags

saas, ai, anthropic

import anthropic

# The SDK retries 429 and 5xx errors automatically (2 retries by default)
client = anthropic.Anthropic(max_retries=5)  # Increase for high-traffic apps

# Disable auto-retry for manual control
client = anthropic.Anthropic(max_retries=0)

const client = new Anthropic({ maxRetries: 5 });

import time
import anthropic

class RateLimitedClient:
    def __init__(self):
        self.client = anthropic.Anthropic(max_retries=0)  # We handle retries
        self.remaining_requests = 100
        self.remaining_tokens = 100000
        self.reset_at = 0.0

    def create_message(self, **kwargs):
        # Pre-check: wait if near limit
        if self.remaining_requests < 3 and time.time() < self.reset_at:
            wait = self.reset_at - time.time()
            print(f"Pre-throttle: waiting {wait:.1f}s")
            time.sleep(wait)

        for attempt in range(5):
            try:
                response = self.client.messages.create(**kwargs)

                # Update from response headers (via _response)
                headers = response._response.headers
                self.remaining_requests = int(headers.get("anthropic-ratelimit-requests-remaining", 100))
                self.remaining_tokens = int(headers.get("anthropic-ratelimit-tokens-remaining", 100000))
                reset = headers.get("anthropic-ratelimit-requests-reset")
                if reset:
                    from datetime import datetime
                    self.reset_at = datetime.fromisoformat(reset.replace("Z", "+00:00")).timestamp()

                return response
            except anthropic.RateLimitError as e:
                retry_after = float(e.response.headers.get("retry-after", 2 ** attempt))
                print(f"429 — retry in {retry_after}s (attempt {attempt + 1})")
                time.sleep(retry_after)

        raise Exception("Exhausted rate limit retries")

import PQueue from 'p-queue';
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic();

// Enforce 50 RPM with concurrency limit
const queue = new PQueue({
  concurrency: 10,
  interval: 60_000,
  intervalCap: 50,
});

async function rateLimitedCall(prompt: string) {
  return queue.add(() =>
    client.messages.create({
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      messages: [{ role: 'user', content: prompt }],
    })
  );
}

// Process 200 prompts without hitting limits
const results = await Promise.all(
  prompts.map(p => rateLimitedCall(p))
);

# Message Batches API: 50% cheaper, no rate limit pressure on real-time quota
batch = client.messages.batches.create(
    requests=[
        {"custom_id": f"req-{i}", "params": {
            "model": "claude-sonnet-4-20250514",
            "max_tokens": 1024,
            "messages": [{"role": "user", "content": prompt}]
        }}
        for i, prompt in enumerate(prompts)
    ]
)

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/.curated/anth-rate-limits of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287