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Get Started Free →Implement Adobe API rate limiting, backoff, and quota management across Firefly, PDF Services, Photoshop, and I/O Events APIs. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Adobe. Trigger with phrases like "adobe rate limit", "adobe throttling", "adobe 429", "adobe retry", "adobe backoff", "adobe quota".
.claude/skills/jeremylongshore-adobe-rate-limits/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 2% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 7% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 14% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 28% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 46% | 0% |
Handle Adobe API rate limits gracefully with exponential backoff, Retry-After header support, and proactive quota management. Each Adobe API has different rate limits.
| API | Limit | Scope | Response | |-----|-------|-------|----------| | Firefly API | ~20 req/min (trial), higher on paid | Per api-key | 429 + Retry-After | | PDF Services | 500 tx/month (free), unlimited (paid) | Per credential | 429 or QUOTA_EXCEEDED | | Photoshop API | Varies by entitlement | Per api-key | 429 + Retry-After | | Lightroom API | Varies by entitlement | Per api-key | 429 + Retry-After | | I/O Events Publishing | 3,000 req/5sec | Per api-key | 429 + Retry-After | | Analytics 2.0 API | 12 req/6sec per user (~120 req/min) | Per user | 429 + Retry-After | | IMS Token Endpoint | ~100 req/min | Per client_id | 429 |
typescript// src/adobe/rate-limiter.ts import { AdobeApiError } from './client'; export async function withAdobeBackoff<T>( operation: () => Promise<T>, config = { maxRetries: 5, baseDelayMs: 1000, maxDelayMs: 60_000 } ): Promise<T> { for (let attempt = 0; attempt <= config.maxRetries; attempt++) { try { return await operation(); } catch (error: any) { if (attempt === config.maxRetries) throw error; // Only retry on 429 and 5xx const status = error.status || error.response?.status; if (status && status !== 429 && (status < 500 || status >= 600)) throw error; // Honor Adobe's Retry-After header (seconds) let delay: number; if (error.retryAfter) { delay = error.retryAfter * 1000; } else { // Exponential backoff with jitter const exponential = config.baseDelayMs * Math.pow(2, attempt); const jitter = Math.random() * config.baseDelayMs; delay = Math.min(exponential + jitter, config.maxDelayMs); } console.warn( `Adobe rate limited (attempt ${attempt + 1}/${config.maxRetries}). ` + `Waiting ${(delay / 1000).toFixed(1)}s...` ); await new Promise(r => setTimeout(r, delay)); } } throw new Error('Unreachable'); }
typescript// Track remaining quota from response headers class AdobeRateTracker { private remaining: number = Infinity; private resetAt: number = 0; updateFromResponse(response: Response): void { const remaining = response.headers.get('Retry-After'); // Adobe primarily uses Retry-After rather than X-RateLimit-* headers // Some APIs (Analytics, Events) include additional rate info if (remaining) { this.remaining = 0; this.resetAt = Date.now() + parseInt(remaining) * 1000; } } async waitIfNeeded(): Promise<void> { if (this.remaining <= 0 && Date.now() < this.resetAt) { const waitMs = this.resetAt - Date.now(); console.log(`Proactively waiting ${waitMs}ms for Adobe rate limit reset`); await new Promise(r => setTimeout(r, waitMs)); this.remaining = Infinity; // Reset after wait } } }
typescriptimport PQueue from 'p-queue'; // Configure queue per API — match to known rate limits const fireflyQueue = new PQueue({ concurrency: 2, // Max concurrent requests interval: 3000, // Time window (ms) intervalCap: 1, // Max requests per interval }); const pdfServicesQueue = new PQueue({ concurrency: 5, interval: 1000, intervalCap: 5, }); const eventsQueue = new PQueue({ concurrency: 10, interval: 5000, intervalCap: 3000, // Match Adobe's 3000/5sec limit }); // Usage async function batchFireflyGenerate(prompts: string[]) { const results = await Promise.all( prompts.map(prompt => fireflyQueue.add(() => withAdobeBackoff(() => generateImage({ prompt })) ) ) ); return results; }
typescript// Track monthly PDF Services usage against free tier limit class PdfServicesQuotaTracker { private transactionsUsed = 0; private readonly monthlyLimit: number; constructor(tier: 'free' | 'paid' = 'free') { this.monthlyLimit = tier === 'free' ? 500 : Infinity; } recordTransaction(): void { this.transactionsUsed++; const remaining = this.monthlyLimit - this.transactionsUsed; if (remaining <= 50) { console.warn(`PDF Services: ${remaining} transactions remaining this month`); } if (remaining <= 0) { throw new Error('PDF Services monthly quota exceeded. Upgrade plan or wait for reset.'); } } getUsage(): { used: number; limit: number; remaining: number } { return { used: this.transactionsUsed, limit: this.monthlyLimit, remaining: Math.max(0, this.monthlyLimit - this.transactionsUsed), }; } }
Retry-After headers| Scenario | Detection | Action | |----------|-----------|--------| | Single 429 | Retry-After header | Wait specified seconds, retry | | Sustained 429s | Multiple retries fail | Reduce concurrency; check tier | | PDF QUOTA_EXCEEDED | Monthly limit hit | Upgrade tier or wait for reset | | Events 429 | 3000/5sec exceeded | Reduce batch size or add queue |
Start with the smallest applicable command or code example already provided in this guide, using a non-production Adobe environment and credentials. Confirm the documented response or validation result before applying the pattern to production.
For security configuration, see adobe-security-basics.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 58,443 | 51,446 | -12% | 1 | 1 | 0% | 5,897 | 6,015 | +2% | 0 | 0 | — |
case-02 | fail→fail | 24,151 | 45,505 | +88% | 1 | 1 | 0% | 4,889 | 4,923 | +1% | 0 | 0 | — |
case-03 | fail→fail | 20,444 | 52,475 | +157% | 1 | 1 | 0% | 4,202 | 5,603 | +33% | 0 | 0 | — |
case-04 | fail→pass | 18,787 | 10,048 | -47% | 1 | 1 | 0% | 3,550 | 3,812 | +7% | 0 | 0 | — |
case-05 | fail→pass | 50,557 | 13,298 | -74% | 1 | 1 | 0% | 3,747 | 4,274 | +14% | 0 | 0 | — |
case-06 | pass→pass | 15,270 | 6,080 | -60% | 1 | 1 | 0% | 2,806 | 3,087 | +10% | 0 | 0 | — |
case-07 | fail→pass | 15,253 | 7,736 | -49% | 1 | 1 | 0% | 2,526 | 3,232 | +28% | 0 | 0 | — |
case-08 | fail→pass | 14,027 | 8,501 | -39% | 1 | 1 | 0% | 2,265 | 3,299 | +46% | 0 | 0 | — |
case-09 | fail→pass | 12,745 | 2,876 | -77% | 1 | 1 | 0% | 2,140 | 2,301 | +8% | 0 | 0 | — |
case-10 | fail→pass | 19,143 | 7,846 | -59% | 1 | 1 | 0% | 2,079 | 3,212 | +54% | 0 | 0 | — |
case-11 | pass→pass | 9,918 | 4,020 | -59% | 1 | 1 | 0% | 1,782 | 2,590 | +45% | 0 | 0 | — |
case-12 | pass→pass | 14,066 | 3,224 | -77% | 1 | 1 | 0% | 2,563 | 2,423 | -5% | 0 | 0 | — |
case-13 | fail→pass | 12,410 | 6,403 | -48% | 1 | 1 | 0% | 2,444 | 3,215 | +32% | 0 | 0 | — |
case-14 | fail→pass | 8,870 | 2,903 | -67% | 1 | 1 | 0% | 1,849 | 2,485 | +34% | 0 | 0 | — |
case-15 | pass→pass | 23,428 | 9,112 | -61% | 1 | 1 | 0% | 3,302 | 3,823 | +16% | 0 | 0 | — |
case-16 | pass→pass | 10,361 | 2,413 | -77% | 1 | 1 | 0% | 1,776 | 2,237 | +26% | 0 | 0 | — |
case-17 | pass→pass | 8,715 | 3,942 | -55% | 1 | 1 | 0% | 1,642 | 2,630 | +60% | 0 | 0 | — |
case-18 | pass→fail | 6,814 | 2,322 | -66% | 1 | 1 | 0% | 1,136 | 2,199 | +94% | 0 | 0 | — |
case-19 | fail→pass | 6,048 | 1,126 | -81% | 1 | 1 | 0% | 955 | 2,021 | +112% | 0 | 0 | — |
case-20 | fail→pass | 13,342 | 2,028 | -85% | 1 | 1 | 0% | 2,375 | 2,196 | -8% | 0 | 0 | — |
case-21 | pass→pass | 11,261 | 12,183 | +8% | 1 | 1 | 0% | 2,153 | 4,341 | +102% | 0 | 0 | — |
case-22 | pass→pass | 27,593 | 17,206 | -38% | 1 | 1 | 0% | 2,959 | 5,244 | +77% | 0 | 0 | — |
case-23 | pass→pass | 16,439 | 14,837 | -10% | 1 | 1 | 0% | 3,127 | 4,646 | +49% | 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. 23 cases were attempted. The headline lift of +43 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
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.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/13/2026 | +59% |
Other measured skills in the registry, with their headline benchmark lift.