Agent skill · data analytics · jeremylongshore
clade-rate-limits
Handle Anthropic rate limits \u2014 understand tiers, implement backoff,\n\
Why this skill is useful
Provides specific implementation patterns for handling Anthropic's rate limits, including custom backoff strategies and throughput optimization techniques.
What it needs
Requires anthropic account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Anthropic Rate Limits Overview Anthropic enforces three types of limits: requests per minute (RPM), input tokens per minute (TPM), and output tokens per minute. Limits depend on your spend tier. Rate Limit Tiers Tier Qualification RPM Input TPM Output TPM ------ -------------- ----- ----------- ------------ Tier 1 Free 50 40,000 8,000 Tier 2 $40+ spend 1,000 80,000 16,000 Tier 3 $200+ spend 2,000 160,000 32,000 Tier 4 $400+ spend 4,000 400,000 80,000 Scale Custom Custom Custom Custom Check your tier: console.anthropic.com → Settings → Limits Response Headers Every API response includes rate limit headers: Built-In SDK Retries The SDK automatically retries 429 and 529 errors with exponential backoff: Custom Backoff Throughput Optimization Strategy Impact ---------- -------- Use Message Batches API Bypasses rate limits entirely (async, 24h SLA) Use prompt caching Cached tokens don't count toward input TPM Use smaller models for simple tasks Lower token counts = more requests per minute Pre-count tokens with countTokens Avoid wasted requests that will fail Queue and batch requests Smooth out bursts Token Counting Python Output Rate limit tier identified from response headers SDK configured with appropriate maxRetries setting Custom backoff implemented with jitter for high-throughput use cases Throughput optimized using batches, caching, or model selection Error Handling Error Cause Solution ------- ------- ---------- API Error Check error type and status code See clade-common-errors Examples See Rate Limit Tiers table, Response Headers section, Built-In SDK Retries, Custom Backoff implementation, and Throughput Optimization strategies above. Resources Rate Limits Docs Message Batches — no rate limits Token Counting Next Steps See clade-cost-tuning for cost optimization strategies. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/clade-rate-limits--bba902