Humanizer

{
  "mcpServers": {
    "notion": {
      "command": "npx",
      "args": ["-y", "@makenotion/mcp-server"],
      "env": { "NOTION_API_KEY": "${NOTION_API_KEY}" }
    },
    "exa": {
      "command": "npx",
      "args": ["-y", "@exa/mcp-server"],
      "env": { "EXA_API_KEY": "${EXA_API_KEY}" }
    }
  }
}

// 1. Load source content
const content = await notion.pages.retrieve({ pageId: draftId });
const text = content.blocks.map(b => b.paragraph.rich_text[0]?.plain_text).join("\n");

// 2. Analyze for AI patterns
const patterns = detectAIPatterns(text);
// Returns: ["significance_inflation", "copula_avoidance", "formulaic_challenges", "ai_vocabulary"]

// 3. Research target voice (optional)
const targetVoice = "tech journalist"; // or retrieve from Notion
const samples = await exa.search(targetVoice, {
  category: "content",
  numResults: 5
});
const voiceProfile = extractVoiceFromSamples(samples);

// 4. Rewrite with LLM
const humanized = await rewrite(text, {
  patternsToFix: patterns,
  tone: voiceProfile || "professional",
  preserveMeaning: true
});

// 5. Store in Notion
const refinedPage = await notion.pages.create({
  parent: { databaseId: refinedContentDbId },
  properties: {
    "Title": { "title": [{ "text": { "content": `Refined: ${content.title}` } }] },
    "Source": { "url": content.url },
    "Patterns Fixed": { "multi_select": patterns.map(p => ({ "name": p })) }
  },
  children: [
    {
      "object": "block",
      "type": "heading_2",
      "heading_2": { "rich_text": [{ "text": { "content": "Original" } }] }
    },
    {
      "object": "block",
      "type": "paragraph",
      "paragraph": { "rich_text": [{ "text": { "content": text } }] }
    },
    {
      "object": "block",
      "type": "heading_2",
      "heading_2": { "rich_text": [{ "text": { "content": "Humanized" } }] }
    },
    {
      "object": "block",
      "type": "paragraph",
      "paragraph": { "rich_text": [{ "text": { "content": humanized } }] }
    }
  ]
});

function detectAIPatterns(text: string): string[] {
  const patterns: string[] = [];
  
  // Significance inflation
  if (text.match(/pivotal|groundbreaking|unprecedented|transformative/gi)) {
    patterns.push("significance_inflation");
  }
  
  // Copula avoidance (serves as, acts as)
  if (text.match(/\b(serves as|acts as|functions as)\b/gi)) {
    patterns.push("copula_avoidance");
  }
  
  // Formulaic challenges
  if (text.match(/despite (challenges|difficulties|obstacles)/gi)) {
    patterns.push("formulaic_challenges");
  }
  
  // AI vocabulary
  const aiWords = ["additionally", "moreover", "furthermore", "testament", "landscape", "realm"];
  if (aiWords.some(w => text.toLowerCase().includes(w))) {
    patterns.push("ai_vocabulary");
  }
  
  // Em dash overuse
  if ((text.match(/—/g) || []).length > 2) {
    patterns.push("em_dash_overuse");
  }
  
  // Filler phrases
  if (text.match(/\b(in order to|due to the fact that|it is important to note)\b/gi)) {
    patterns.push("filler_phrases");
  }
  
  return patterns;
}