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Get Started Free →Implement AssemblyAI rate limiting, backoff, and queue-based throttling. Use when handling rate limit errors, implementing retry logic, or managing concurrent transcription throughput. Trigger with phrases like "assemblyai rate limit", "assemblyai throttling", "assemblyai 429", "assemblyai retry", "assemblyai backoff".
.claude/skills/jeremylongshore-assemblyai-rate-limits/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 46% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 41% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 48% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 116% | 0% |
Control capacity with explicit account limits, queues, and retry budgets. Keep data, credentials, spend, and replay decisions separately governed.
AssemblyAI documents 20,000 API requests per five minutes plus operation-specific concurrency limits. Limits apply at account level; project keys mirror capacity rather than multiply it. Actual concurrency and autoscaling are account-specific, so use current dashboard and documentation evidence.
For live work, inject ASSEMBLYAI_API_KEY from an approved secret manager and send the raw value only in the AssemblyAI Authorization header to the configured first-party host. Never print, commit, place in a URL, or expose it to an untrusted client. Callback secrets and temporary streaming tokens are separate credentials.
Retry-After or capped exponential backoff with jitter.Use Read, Glob, and Grep to inspect repository code, configuration, fixtures, and evidence. Use Write and Edit only for approved implementation or documentation changes. Do not call AssemblyAI, upload audio, open a streaming session, mint a token, replay a callback, deploy, rotate a key, or delete a transcript merely because this skill was invoked.
Require an accountable owner before live audio processing, production credential or endpoint changes, paid model or capacity changes, content retention, callback replay, deployment, or deletion. Read-only repository inspection and synthetic offline validation do not authorize live vendor actions.
Return the operation scope, environment, region, contract surface, authorization class, model and feature decisions, deterministic validation results, content-free identifiers, risks, cleanup or rollback state, and a concise pass/fail receipt. Exclude credentials, signed URLs, audio, transcript text, prompts, and customer-derived content.
Rerun the smallest relevant deterministic check, compare actual state with the requested outcome and current first-party contract, verify sensitive fields are absent from evidence, and confirm rollback, termination, or deletion state before reporting success.
Review the dated first-party evidence map before relying on any model, parameter, limit, price, region, or lifecycle claim.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-04 | pass→pass | 11,778 | 11,379 | -3% | 1 | 1 | 0% | 2,367 | 4,023 | +70% | 0 | 0 | — |
case-01 | fail→fail | 18,283 | 12,995 | -29% | 1 | 1 | 0% | 3,198 | 4,457 | +39% | 0 | 0 | — |
case-02 | fail→pass | 12,470 | 10,493 | -16% | 1 | 1 | 0% | 2,597 | 3,802 | +46% | 0 | 0 | — |
case-03 | fail→fail | 13,794 | 12,995 | -6% | 1 | 1 | 0% | 2,841 | 4,375 | +54% | 0 | 0 | — |
case-05 | pass→pass | 9,808 | 11,215 | +14% | 1 | 1 | 0% | 1,913 | 3,788 | +98% | 0 | 0 | — |
case-06 | pass→pass | 13,450 | 10,495 | -22% | 1 | 1 | 0% | 2,798 | 3,921 | +40% | 0 | 0 | — |
case-07 | fail→pass | 13,116 | 7,612 | -42% | 1 | 1 | 0% | 2,439 | 3,141 | +29% | 0 | 0 | — |
case-08 | fail→pass | 11,140 | 9,011 | -19% | 1 | 1 | 0% | 2,559 | 3,619 | +41% | 0 | 0 | — |
case-09 | fail→pass | 8,701 | 2,385 | -73% | 1 | 1 | 0% | 1,409 | 2,079 | +48% | 0 | 0 | — |
case-10 | fail→pass | 7,210 | 4,780 | -34% | 1 | 1 | 0% | 1,174 | 2,539 | +116% | 0 | 0 | — |
case-11 | fail→pass | 11,656 | 8,102 | -30% | 1 | 1 | 0% | 1,798 | 3,131 | +74% | 0 | 0 | — |
case-12 | fail→pass | 14,235 | 6,935 | -51% | 1 | 1 | 0% | 2,360 | 3,024 | +28% | 0 | 0 | — |
case-13 | pass→fail | 18,886 | 13,543 | -28% | 1 | 1 | 0% | 3,534 | 4,425 | +25% | 0 | 0 | — |
case-14 | fail→pass | 19,814 | 1,924 | -90% | 1 | 1 | 0% | 3,621 | 1,928 | -47% | 0 | 0 | — |
case-15 | fail→pass | 17,922 | 5,014 | -72% | 1 | 1 | 0% | 1,845 | 2,606 | +41% | 0 | 0 | — |
case-16 | pass→pass | 8,488 | 1,349 | -84% | 1 | 1 | 0% | 1,457 | 1,832 | +26% | 0 | 0 | — |
case-17 | fail→pass | 12,627 | 5,581 | -56% | 1 | 1 | 0% | 2,277 | 2,700 | +19% | 0 | 0 | — |
case-18 | fail→fail | 8,407 | 7,447 | -11% | 1 | 1 | 0% | 1,484 | 3,195 | +115% | 0 | 0 | — |
case-19 | fail→fail | 9,032 | 4,884 | -46% | 1 | 1 | 0% | 1,522 | 2,465 | +62% | 0 | 0 | — |
case-20 | fail→pass | 8,403 | 1,475 | -82% | 1 | 1 | 0% | 1,448 | 1,830 | +26% | 0 | 0 | — |
case-21 | fail→pass | 12,393 | 4,959 | -60% | 1 | 1 | 0% | 2,110 | 2,561 | +21% | 0 | 0 | — |
case-22 | fail→pass | 8,593 | 1,688 | -80% | 1 | 1 | 0% | 1,308 | 1,883 | +44% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +55 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
The publisher has shipped newer versions since this run, so these numbers describe v1, not the version currently listed.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.