Skills

Comment Mining

Use when the user wants to mine comments and replies for audience reactions, customer...

Install

npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -g -a claude-code -y
Category
Media
Updated
2mo ago
License
MIT
Context cost
Lightabout 837 tokens
Runs scripts
No, instructions only

What it does

Use when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or voice-of-customer insights from public social posts and videos.

Comment Mining

Overview

Mine public comments for what people actually ask, complain about, want, misunderstand, or repeat. The output should help with product research, content ideas, copywriting, objection handling, and audience understanding.

When to Use

Use this skill when the user asks to:

  • analyze comments on a TikTok, YouTube video, Instagram Reel, Facebook post, Reddit post, or Rumble video
  • find audience questions, objections, complaints, or buying intent
  • extract voice-of-customer language
  • find content ideas from comments
  • understand sentiment around a post, creator, product, or topic

Comment Sources

PlatformEndpoint
TikTok comments/v1/tiktok/video/comments
TikTok replies/v1/tiktok/video/comment/replies
YouTube comments/v1/youtube/video/comments
YouTube replies/v1/youtube/video/comment/replies
Instagram comments/v2/instagram/post/comments
Facebook comments/v1/facebook/post/comments
Facebook replies/v1/facebook/post/comment/replies
Reddit comments/v1/reddit/post/comments
Rumble comments/v1/rumble/video/comments

Workflow

  1. Fetch comments

    • Use the post/video URL whenever possible.
    • Paginate when the endpoint supports it and the user wants depth.
    • Preserve comment text, author if public, like/upvote count, timestamp, and source URL.
  2. Clean lightly

    • Remove obvious spam/duplicates.
    • Keep slang, misspellings, and emotional wording if it is useful customer language.
    • Do not over-normalize exact quotes.
  3. Classify each useful comment Use these buckets:

    • questions
    • objections
    • complaints/pain points
    • praise
    • confusion
    • requests/feature ideas
    • buying intent
    • controversy/debate
    • jokes/memes/culture signals
  4. Cluster themes

    • Group similar comments.
    • Score themes by frequency and intensity.
    • Highlight exact quotes for each theme.
Read the whole SKILL.md on GitHub

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