tessl install github:jeremylongshore/claude-code-plugins-plus-skills --skill instantly-performance-tuninggithub.com/jeremylongshore/claude-code-plugins-plus-skills
Optimize Instantly API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Instantly integrations. Trigger with phrases like "instantly performance", "optimize instantly", "instantly latency", "instantly caching", "instantly slow", "instantly batch".
Review Score
88%
Validation Score
12/16
Implementation Score
88%
Activation Score
90%
Optimize Instantly 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 cachedInstantlyRequest<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 instantlyLoader = new DataLoader<string, any>(
async (ids) => {
// Batch fetch from Instantly
const results = await instantlyClient.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([
instantlyLoader.load('id-1'),
instantlyLoader.load('id-2'),
instantlyLoader.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 InstantlyClient({
apiKey: process.env.INSTANTLY_API_KEY!,
httpAgent: agent,
});async function* paginatedInstantlyList<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 paginatedInstantlyList(cursor =>
instantlyClient.list({ cursor, limit: 100 })
)) {
await process(item);
}async function measuredInstantlyCall<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 Instantly 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>) =>
measuredInstantlyCall(name, () =>
cachedInstantlyRequest(`cache:${name}`, fn)
);For cost optimization, see instantly-cost-tuning.