Agent skill
grammarly-sdk-patterns
Apply production-ready Grammarly SDK patterns for TypeScript and Python. Use when implementing Grammarly integrations, refactoring SDK usage, or establishing team coding standards for Grammarly. Trigger with phrases like "grammarly SDK patterns", "grammarly best practices", "grammarly code patterns", "idiomatic grammarly".
Install this agent skill to your Project
npx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/grammarly-pack/skills/grammarly-sdk-patterns
SKILL.md
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.
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