Skills Development Optimizing Grammarly API Performance

Optimizing Grammarly API Performance

v20260423
grammarly-performance-tuning
This guide provides techniques to optimize Grammarly API interactions, focusing on reducing latency and improving throughput. Learn how to implement efficient caching strategies (like LRU cache) for repeated score checks and how to execute multiple API calls in parallel using Promise.all. Use this when experiencing slow response times or needing cost/performance improvements in Grammarly integrations.
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Overview

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 detect in parallel (they're independent)
async function fullAudit(text: string, token: string) {
  const [score, ai] = await Promise.all([
    grammarlyClient.score(text),
    grammarlyClient.detectAI(text),
  ]);
  return { score, ai };
}

Resources

Next Steps

For cost optimization, see grammarly-cost-tuning.

Info
Category Development
Name grammarly-performance-tuning
Version v20260423
Size 1.77KB
Updated At 2026-04-28
Language