| name | comment-mining |
| description | 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. |
| allowed-tools | Bash, Read, Write, WebFetch |
| version | 1.0.0 |
| author | ScrapeCreators |
| license | MIT |
| homepage | https://scrapecreators.com |
| repository | https://github.com/ScrapeCreators/social-media-research-skills |
| metadata | {"openclaw":{"requires":{"env":"[Truncated]"},"primaryEnv":"SCRAPECREATORS_API_KEY","homepage":"https://scrapecreators.com","tags":["social-media","research","scrapecreators"]}} |
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
| Platform | Endpoint |
|---|
| 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
-
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.
-
Clean lightly
- Remove obvious spam/duplicates.
- Keep slang, misspellings, and emotional wording if it is useful customer language.
- Do not over-normalize exact quotes.
-
Classify each useful comment
Use these buckets:
- questions
- objections
- complaints/pain points
