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效率与协作 · SKILL.md

clade-load-scale

clade-load-scale

【效率与协作】Scale Claude usage for high-throughput applications — batches, queues, Use when working with load-scale patterns. concurrency control, and tier upgrades. Trigger with "anthropic scale", "claude high volume", "anthropic throughput", "scale claude api", "anthropic concurrent requests".

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技能说明

GitHub

name: clade-load-scale description: "Scale Claude usage for high-throughput applications \u2014 batches,
\ queues,\nUse when working with load-scale patterns.\nconcurrency control, and
\ tier upgrades.\nTrigger with "anthropic scale", "claude high volume", "anthropic
\ throughput",\n"scale claude api", "anthropic concurrent requests".\n" allowed-tools: Read, Write, Edit version: 1.1.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

  • saas
  • anthropic
  • claude
  • scale
  • throughput compatibility: Designed for Claude Code

Anthropic Load & Scale

Overview

Scale Claude usage for high-throughput applications. Covers four strategies: Message Batches (10K requests, 50% off, no rate limits), request queues with concurrency control via p-limit, tier upgrades (Tier 1-4 + Scale), and model selection for throughput (Haiku is 3-4x faster than Sonnet).

Scaling Strategies

Instructions

Step 1: Message Batches (Best for Bulk)

// 10K requests per batch, 50% cheaper, no rate limits
const batch = await client.messages.batches.create({
  requests: items.map((item, i) => ({
    custom_id: `${i}`,
    params: { model: 'claude-sonnet-4-20250514', max_tokens: 1024, messages: [{ role: 'user', content: item }] },
  })),
});
// Process up to 100 concurrent batches

Step 2: Request Queue with Concurrency Control

import pLimit from 'p-limit';

// Match your rate limit tier
const limit = pLimit(10); // 10 concurrent requests

const results = await Promise.all(
  inputs.map(input =>
    limit(() => client.messages.create({
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      messages: [{ role: 'user', content: input }],
    }))
  )
);

Step 3: Tier Upgrades

Increase your spending to unlock higher tiers:

TierRPMInput TPMHow to Qualify
15040KFree
21,00080K$40+ total spend
32,000160K$200+ total spend
44,000400K$400+ total spend
ScaleCustomCustomContact sales

Step 4: Model Selection for Throughput

// Haiku processes 3-4x faster than Sonnet, 8x faster than Opus
// Use the fastest model that meets quality requirements
const model = taskComplexity === 'simple' ? 'claude-haiku-4-5-20251001' : 'claude-sonnet-4-20250514';

Monitoring at Scale

// Track throughput metrics
let requestCount = 0;
let tokenCount = 0;

setInterval(() => {
  console.log(`Throughput: ${requestCount} req/min, ${tokenCount} tokens/min`);
  requestCount = 0;
  tokenCount = 0;
}, 60_000);

Output

  • Batch processing configured for bulk workloads (50% cheaper, no rate limits)
  • Concurrency-controlled request queue matching rate limit tier
  • Rate limit tier upgraded by increasing cumulative spend
  • Throughput metrics tracked (requests/min, tokens/min)

Error Handling

ErrorCauseSolution
API ErrorCheck error type and status codeSee clade-common-errors

Examples

See Message Batches example, p-limit concurrency control, Tier Upgrades table, and Monitoring at Scale metrics tracking above.

Resources

Next Steps

See clade-reliability-patterns for fault-tolerant high-scale patterns.

Prerequisites

  • Completed clade-rate-limits for understanding tier limits
  • High-volume use case requiring more than basic tier throughput
  • For batches: tolerance for async processing (24h SLA)
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