Skip to content
Back to skills

Rate Limit Handler

ASecurity

Adds retry-with-backoff, Retry-After handling, and client-side throttling so a caller stays under an upstream API's rate limits instead of hammering it. Use when you call a rate-limited or quota-enforced third-party API, see 429 or 503 responses or Retry-After headers, or have a worker fleet that needs to share one upstream's quota. Do NOT use to fail fast when a dependency is down - use circuit-breaker-builder instead; do NOT use to scaffold the HTTP client itself - use api-client-generator ...

  • 18 stars
  • 0 votes
  • 0 copies
  • 5 views
  • Added September 6, 2026
ai-agentsgoreactapi

Works with

  • cli
  • api

Security analysis

A100/100

Scanned October 5, 2026

npx -y skills add SkillMedev/skills --skill rate-limit-handler --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Rate Limit Handler?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Rate Limit Handler
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/skillmedev-rate-limit-handler/badge)](https://www.skillsdirectory.com/skills/skillmedev-rate-limit-handler)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: rate-limit-handler
description: Adds retry-with-backoff, Retry-After handling, and client-side throttling so a caller stays under an upstream API's rate limits instead of hammering it. Use when you call a rate-limited or quota-enforced third-party API, see 429 or 503 responses or Retry-After headers, or have a worker fleet that needs to share one upstream's quota. Do NOT use to fail fast when a dependency is down - use circuit-breaker-builder instead; do NOT use to scaffold the HTTP client itself - use api-client-generator instead.
metadata:
  title: "Rate Limit Handler"
---
# Rate Limit Handler

Stay under an upstream's quota by backing off cooperatively, obeying what the server tells you, and de-synchronizing your fleet - retrying harder is how a transient limit becomes an outage.

## Workflow

1. **Classify the response before reacting.** Retry only on 429, 502, 503, 504, and connection/timeout errors. Never retry 400, 401, 403, 404, or 422 - they will fail identically. Retry only idempotent or idempotency-keyed operations; a bare non-idempotent POST can duplicate effects.
2. **Honor the server first.** If the response carries `Retry-After`, obey it exactly and skip local backoff math - parse both the delta-seconds and the HTTP-date form. Read `X-RateLimit-Remaining` and `X-RateLimit-Reset` proactively and slow down as remaining approaches zero rather than waiting to be rejected - throttling when remaining drops below ~10% of the window's quota is a reasonable trigger.
3. **Back off with full jitter when there is no `Retry-After`.** Compute `delay = base * 2^attempt` with a base of 100-500ms, clamp it to a max (e.g. 30-60s), then sleep a uniform random value between 0 and that clamped cap - not the cap itself. Full jitter is what de-synchronizes many clients retrying the same downed service.
4. **Bound the retries.** Cap both the attempt count (e.g. 5) and the total elapsed budget (e.g. 30-60s, and always below the caller's own timeout) so a request fails fast instead of hanging a caller for minutes. Surface the final failure to the caller; do not swallow it.
5. **Throttle proactively with a token bucket.** Put a client-side limiter in front of the API sized to roughly 80% of the published quota - the headroom absorbs retries, clock skew, and other callers you forgot about - so bursts are smoothed and you stay under the limit by design rather than reacting to 429s. When many workers hit one upstream, back the bucket with a shared store (e.g. Redis) so the aggregate rate - not the per-process rate - stays bounded.
6. **Make it observable.** Emit metrics for retry count, backoff duration, and 429 rate. A rising 429 rate is the early signal to lower concurrency or request a quota increase before users see errors; sustained 429s above ~1% of requests means the token bucket is mis-sized or missing.

## Deliverable

Produce the retry/throttle layer (a wrapper, interceptor, or middleware around the upstream client) plus a short configuration summary stating: the retryable status set, base delay, cap, and jitter mode, the attempt and total-time budgets, the token-bucket rate and burst size relative to the published quota, whether the bucket is per-process or shared across the fleet, and the metrics emitted. The summary is what the next engineer tunes when the upstream changes its limits.

## Quality bar

- No fixed-delay or no-jitter retry loop survives - every backoff path applies jitter.
- `Retry-After` always wins over computed backoff.
- Every retry path is bounded by both attempt count and total time budget.
- Non-idempotent operations are never retried without an idempotency key.
- The 4xx set above is never retried.

## Do NOT

- Do NOT retry on 4xx client errors (except 429) - the request is malformed or unauthorized and will fail again.
- Do NOT use fixed or cap-only backoff - synchronized clients recreate the thundering herd you are trying to avoid.
- Do NOT retry forever or without a total-time budget.
- Do NOT enforce per-process limits when a fleet shares one quota - the aggregate will still blow the limit.
- Do NOT add the full backoff-plus-bucket stack to a single best-effort background call; let it fail and move on, and reserve the machinery for hot paths and high-volume integrations.

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.