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Grammarly data handling

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/grammarly-pack/skills/grammarly-data-handling

'Implement Grammarly data handling patterns for document processing.From its SKILL.md

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill grammarly-data-handling

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The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.3 KB, 458 tokens by cl100k_base, as published. Nobody here has run it

Grammarly Data Handling

Overview

Handle large documents, text chunking, and data pipelines for Grammarly API. The API accepts max 100,000 characters (4 MB) with a minimum of 30 words.

Instructions

Step 1: Text Chunking

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

Step 2: Aggregate Scores Across Chunks

function aggregateScores(scores: any[]): any {
  const avg = (arr: number[]) => arr.reduce((a, b) => a + b, 0) / arr.length;
  return {
    overallScore: Math.round(avg(scores.map(s => s.overallScore))),
    correctness: Math.round(avg(scores.map(s => s.correctness))),
    clarity: Math.round(avg(scores.map(s => s.clarity))),
    engagement: Math.round(avg(scores.map(s => s.engagement))),
    tone: Math.round(avg(scores.map(s => s.tone))),
    chunkCount: scores.length,
  };
}

Step 3: File Processing Pipeline

import fs from 'fs';

async function scoreFile(filePath: string, token: string) {
  const text = fs.readFileSync(filePath, 'utf-8');
  const chunks = chunkText(text);
  const scores = [];
  for (const chunk of chunks) {
    if (chunk.split(/\s+/).length >= 30) {
      scores.push(await grammarlyClient.score(chunk));
    }
  }
  return aggregateScores(scores);
}

Resources

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