Optimize Clay API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Clay integrations. Trigger with phrases like "clay performance", "optimize clay", "clay latency", "clay caching", "clay slow", "clay batch".
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill clay-performance-tuning92
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Validation for skill structure
Optimize Clay API performance with caching, batching, and connection pooling.
| Operation | P50 | P95 | P99 |
|---|---|---|---|
| Read | 50ms | 150ms | 300ms |
| Write | 100ms | 250ms | 500ms |
| List | 75ms | 200ms | 400ms |
import { LRUCache } from 'lru-cache';
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 60000, // 1 minute
updateAgeOnGet: true,
});
async function cachedClayRequest<T>(
key: string,
fetcher: () => Promise<T>,
ttl?: number
): Promise<T> {
const cached = cache.get(key);
if (cached) return cached as T;
const result = await fetcher();
cache.set(key, result, { ttl });
return result;
}import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL);
async function cachedWithRedis<T>(
key: string,
fetcher: () => Promise<T>,
ttlSeconds = 60
): Promise<T> {
const cached = await redis.get(key);
if (cached) return JSON.parse(cached);
const result = await fetcher();
await redis.setex(key, ttlSeconds, JSON.stringify(result));
return result;
}import DataLoader from 'dataloader';
const clayLoader = new DataLoader<string, any>(
async (ids) => {
// Batch fetch from Clay
const results = await clayClient.batchGet(ids);
return ids.map(id => results.find(r => r.id === id) || null);
},
{
maxBatchSize: 100,
batchScheduleFn: callback => setTimeout(callback, 10),
}
);
// Usage - automatically batched
const [item1, item2, item3] = await Promise.all([
clayLoader.load('id-1'),
clayLoader.load('id-2'),
clayLoader.load('id-3'),
]);import { Agent } from 'https';
// Keep-alive connection pooling
const agent = new Agent({
keepAlive: true,
maxSockets: 10,
maxFreeSockets: 5,
timeout: 30000,
});
const client = new ClayClient({
apiKey: process.env.CLAY_API_KEY!,
httpAgent: agent,
});async function* paginatedClayList<T>(
fetcher: (cursor?: string) => Promise<{ data: T[]; nextCursor?: string }>
): AsyncGenerator<T> {
let cursor: string | undefined;
do {
const { data, nextCursor } = await fetcher(cursor);
for (const item of data) {
yield item;
}
cursor = nextCursor;
} while (cursor);
}
// Usage
for await (const item of paginatedClayList(cursor =>
clayClient.list({ cursor, limit: 100 })
)) {
await process(item);
}async function measuredClayCall<T>(
operation: string,
fn: () => Promise<T>
): Promise<T> {
const start = performance.now();
try {
const result = await fn();
const duration = performance.now() - start;
console.log({ operation, duration, status: 'success' });
return result;
} catch (error) {
const duration = performance.now() - start;
console.error({ operation, duration, status: 'error', error });
throw error;
}
}Measure current latency for critical Clay operations.
Add response caching for frequently accessed data.
Use DataLoader or similar for automatic request batching.
Configure connection pooling with keep-alive.
| Issue | Cause | Solution |
|---|---|---|
| Cache miss storm | TTL expired | Use stale-while-revalidate |
| Batch timeout | Too many items | Reduce batch size |
| Connection exhausted | No pooling | Configure max sockets |
| Memory pressure | Cache too large | Set max cache entries |
const withPerformance = <T>(name: string, fn: () => Promise<T>) =>
measuredClayCall(name, () =>
cachedClayRequest(`cache:${name}`, fn)
);For cost optimization, see clay-cost-tuning.
22fc789
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