| name | grammarly-performance-tuning |
| description | Optimize Grammarly API performance with caching, batching, and connection pooling.
Use when experiencing slow API responses, implementing caching strategies,
or optimizing request throughput for Grammarly integrations.
Trigger with phrases like "grammarly performance", "optimize grammarly",
"grammarly latency", "grammarly caching", "grammarly slow", "grammarly batch".
|
| allowed-tools | Read, Write, Edit |
| version | 1.8.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| tags | ["saas","grammarly","writing"] |
| compatibility | Designed for Claude Code |
Grammarly Performance Tuning
Latency Benchmarks
| API | Typical Latency | Notes |
|---|
| Writing Score | 1-3s | Depends on text length |
| AI Detection | 1-2s | Fast for short text |
| Plagiarism | 10-60s | Async, requires polling |
Instructions
Cache Score Results
import { LRUCache } from 'lru-cache';
import { createHash } from 'crypto';
const scoreCache = new LRUCache<string, any>({ max: 500, ttl: 3600000 });
async function cachedScore(text: string, token: string) {
const key = createHash('sha256').update(text).digest('hex');
const cached = scoreCache.get(key);
if (cached) return cached;
const score = await grammarlyClient.score(text);
scoreCache.set(key, score);
return score;
}
Parallel API Calls
() {
[score, ai] = .([
grammarlyClient.(text),
grammarlyClient.(text),
]);
{ score, ai };
}