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Grammarly sdk patterns

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/grammarly-pack/skills/grammarly-sdk-patterns

'Apply production-ready Grammarly SDK patterns for TypeScript and Python.From its SKILL.md

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill grammarly-sdk-patterns

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SKILL.md

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Grammarly SDK Patterns

Overview

Production patterns for Grammarly API: typed client, token management, text chunking for large documents, and Python integration.

Instructions

Step 1: Typed API Client

class GrammarlyClient {
  private token: string;
  private expiresAt: number = 0;
  private base = 'https://api.grammarly.com/ecosystem/api';

  constructor(private clientId: string, private clientSecret: string) {}

  private async ensureToken() {
    if (Date.now() < this.expiresAt - 60000) return;
    const res = await fetch(`${this.base}/v1/oauth/token`, {
      method: 'POST',
      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
      body: new URLSearchParams({ grant_type: 'client_credentials', client_id: this.clientId, client_secret: this.clientSecret }),
    });
    const { access_token, expires_in } = await res.json();
    this.token = access_token;
    this.expiresAt = Date.now() + expires_in * 1000;
  }

  async score(text: string) {
    await this.ensureToken();
    const res = await fetch(`${this.base}/v2/scores`, {
      method: 'POST',
      headers: { 'Authorization': `Bearer ${this.token}`, 'Content-Type': 'application/json' },
      body: JSON.stringify({ text }),
    });
    return res.json();
  }

  async detectAI(text: string) {
    await this.ensureToken();
    const res = await fetch(`${this.base}/v1/ai-detection`, {
      method: 'POST',
      headers: { 'Authorization': `Bearer ${this.token}`, 'Content-Type': 'application/json' },
      body: JSON.stringify({ text }),
    });
    return res.json();
  }
}

Step 2: Text Chunking for Large Documents

function chunkText(text: string, maxChars = 90000): string[] {
  if (text.length <= maxChars) return [text];
  const chunks: string[] = [];
  const paragraphs = text.split('\n\n');
  let current = '';
  for (const p of paragraphs) {
    if ((current + '\n\n' + p).length > maxChars) {
      if (current) chunks.push(current);
      current = p;
    } else {
      current = current ? current + '\n\n' + p : p;
    }
  }
  if (current) chunks.push(current);
  return chunks;
}

Step 3: Python Client

import os, requests
from dotenv import load_dotenv

load_dotenv()

class GrammarlyClient:
    BASE = 'https://api.grammarly.com/ecosystem/api'

    def __init__(self):
        self.token = None
        self._authenticate()

    def _authenticate(self):
        r = requests.post(f'{self.BASE}/v1/oauth/token', data={
            'grant_type': 'client_credentials',
            'client_id': os.environ['GRAMMARLY_CLIENT_ID'],
            'client_secret': os.environ['GRAMMARLY_CLIENT_SECRET'],
        })
        self.token = r.json()['access_token']

    def score(self, text: str):
        r = requests.post(f'{self.BASE}/v2/scores',
            headers={'Authorization': f'Bearer {self.token}', 'Content-Type': 'application/json'},
            json={'text': text})
        return r.json()

Resources

Next Steps

Apply patterns in grammarly-core-workflow-a.

What ships with it

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