claw-mcp-toolkit

Instructions

Implementation Reference

• src/modules/social.ts:61-75 (handler)

  The 'social_engagement_analyzer' tool handler implementation, calculating engagement rates and providing recommendations.

  server.tool("social_engagement_analyzer", "Analyze engagement patterns for optimal posting strategy", {
    followers: z.number().default(1000).describe("Your follower count"),
    avg_likes: z.number().default(10).describe("Average likes per post"),
    avg_replies: z.number().default(2).describe("Average replies per post")
  }, async ({ followers, avg_likes, avg_replies }) => {
    const engRate = ((avg_likes + avg_replies) / followers * 100);
    const rating = engRate > 5 ? "EXCELLENT" : engRate > 3 ? "GOOD" : engRate > 1 ? "AVERAGE" : "LOW";
    const recsMap: Record<string, string> = {
      "EXCELLENT": "Keep doing what you're doing. Focus on threads and data-driven content.",
      "GOOD": "Increase posting frequency. Add more contrarian takes and data posts.",
      "AVERAGE": "Focus on value-first content. Study top accounts in your niche. Post 2-3x/day.",
      "LOW": "Rebuild strategy: 80% value, 20% promo. Engage with 20 accounts daily before posting."
    };
    return { content: [{ type: "text", text: `**Engagement Analysis**\n\nFollowers: ${followers.toLocaleString()}\nAvg Likes: ${avg_likes}\nAvg Replies: ${avg_replies}\n**Engagement Rate**: ${engRate.toFixed(2)}% (${rating})\n\n**Recommendation**: ${recsMap[rating]}\n\n**Benchmarks**:\n- Twitter avg: 0.5-1%\n- Good: 1-3%\n- Viral potential: 3-5%\n- Influencer tier: 5%+` }] };
  });