Mine comments and replies for audience reactions

Comment mining

by ScrapeCreators · MIT license · ★ 2,619 on GitHub · v1.0.0 · updated Aug 26

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.

---
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:
        - SCRAPECREATORS_API_KEY
    primaryEnv: SCRAPECREATORS_API_KEY
    homepage: https://scrapecreators.com
    tags:

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.

The SKILL.md below is the copy AgentAlley read and checked. The repo has changed it since; the other files are from commit 64ba7b4.

Manual install (npx, ZIP)

Claude Codenpx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -g -a claude-code

Claude Code (manual)

mkdir -p ~/.claude/skills && curl -sL https://codeload.github.com/ScrapeCreators/social-media-research-skills/tar.gz/64ba7b4dea71 \
  | tar -xz -C ~/.claude/skills --strip-components=2 social-media-research-skills-64ba7b4dea71/skills/comment-mining

Windows (PowerShell)

New-Item -ItemType Directory -Force "$HOME\.claude\skills" | Out-Null; Invoke-WebRequest "https://m.agentalley.io/zip/090ea2450a430990f36b/comment-mining.zip" -OutFile "$env:TEMP\comment-mining.zip"; Expand-Archive "$env:TEMP\comment-mining.zip" -DestinationPath "$HOME\.claude\skills" -Force

Claude.ai / desktopDownload the ZIP and upload it under Settings → Capabilities → Skills.

Codex, Cursor, other agentsPoint them at SKILL.md. The other files are plain text.

Connects with Agent Alley MCP · agentalley.io/mcp

Files included

SKILL.md4.0 KB

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ScrapeCreators/64ba7b41 file

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SKILL.md

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PreviewCode

Outline

RawView on GitHub

Comment Mining

Overview

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
- praise
- confusion
- requests/feature ideas
- buying intent
- controversy/debate
- jokes/memes/culture signals
Cluster themes
- Group similar comments.
- Score themes by frequency and intensity.
- Highlight exact quotes for each theme.
Turn insights into actions Depending on the user's goal, produce:
- content ideas
- FAQ ideas
- landing page copy angles
- product ideas
- objection-handling bullets
- sales/support notes

Output Format

# Comment Mining Report

## Summary
- Source(s): {urls}
- Comments analyzed: {count}
- Confidence: High/Medium/Low

## Top Themes
| Theme | Type | Frequency | Intensity | Representative quote |
|---|---|---:|---|---|

## Audience Questions
- "..."

## Objections and Concerns
- **Objection:** ...
  - Evidence: "..."
  - Response angle: ...

## Buying Intent / Demand Signals
- "..."

## Exact Language to Reuse
- "..."
- "..."

## Content Ideas From Comments
1. ...
2. ...

Quality Guardrails

Label sample size and confidence.
Separate one loud comment from a repeated pattern.
Preserve exact quotes for useful language.
Avoid claiming broad market sentiment from one post's comments.
Call out moderation/platform bias when relevant.

Common Pitfalls

Do not flatten comments into generic sentiment. The value is in questions, objections, and exact wording.
Do not include personally identifying details unless they are already public and necessary.
Do not treat bot/spam comments as audience signal.
Do not skip Reddit post context. For Reddit, read both the original post and comments.

1	---
2	name: comment-mining
3	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.
4	allowed-tools: Bash, Read, Write, WebFetch
5
6	version: 1.0.0
7	author: ScrapeCreators
8	license: MIT
9	homepage: https://scrapecreators.com
10	repository: https://github.com/ScrapeCreators/social-media-research-skills
11	metadata:
12	openclaw:
13	requires:
14	env:
15	- SCRAPECREATORS_API_KEY
16	primaryEnv: SCRAPECREATORS_API_KEY
17	homepage: https://scrapecreators.com
18	tags:
19	- social-media
20	- research
21	- scrapecreators
22	---
23
24	# Comment Mining
25
26	## Overview
27
28	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.
29
30	## When to Use
31
32	Use this skill when the user asks to:
33
34	- analyze comments on a TikTok, YouTube video, Instagram Reel, Facebook post, Reddit post, or Rumble video
35	- find audience questions, objections, complaints, or buying intent
36	- extract voice-of-customer language
37	- find content ideas from comments
38	- understand sentiment around a post, creator, product, or topic
39
40	## Comment Sources
41
42	\| Platform \| Endpoint \|
43	\|---\|---\|
44	\| TikTok comments \| `/v1/tiktok/video/comments` \|
45	\| TikTok replies \| `/v1/tiktok/video/comment/replies` \|
46	\| YouTube comments \| `/v1/youtube/video/comments` \|
47	\| YouTube replies \| `/v1/youtube/video/comment/replies` \|
48	\| Instagram comments \| `/v2/instagram/post/comments` \|
49	\| Facebook comments \| `/v1/facebook/post/comments` \|
50	\| Facebook replies \| `/v1/facebook/post/comment/replies` \|
51	\| Reddit comments \| `/v1/reddit/post/comments` \|
52	\| Rumble comments \| `/v1/rumble/video/comments` \|
53
54	## Workflow
55
56	1. Fetch comments
57	- Use the post/video URL whenever possible.
58	- Paginate when the endpoint supports it and the user wants depth.
59	- Preserve comment text, author if public, like/upvote count, timestamp, and source URL.
60
61	2. Clean lightly
62	- Remove obvious spam/duplicates.
63	- Keep slang, misspellings, and emotional wording if it is useful customer language.
64	- Do not over-normalize exact quotes.
65
66	3. Classify each useful comment
67	Use these buckets:
68	- questions
69	- objections
70	- complaints/pain points
71	- praise
72	- confusion
73	- requests/feature ideas
74	- buying intent
75	- controversy/debate
76	- jokes/memes/culture signals
77
78	4. Cluster themes
79	- Group similar comments.
80	- Score themes by frequency and intensity.
81	- Highlight exact quotes for each theme.
82
83	5. Turn insights into actions
84	Depending on the user's goal, produce:
85	- content ideas
86	- FAQ ideas
87	- landing page copy angles
88	- product ideas
89	- objection-handling bullets
90	- sales/support notes
91
92	## Output Format
93
94	```markdown
95	# Comment Mining Report
96
97	## Summary
98	- Source(s): {urls}
99	- Comments analyzed: {count}
100	- Confidence: High/Medium/Low
101
102	## Top Themes
103	\| Theme \| Type \| Frequency \| Intensity \| Representative quote \|
104	\|---\|---\|---:\|---\|---\|
105
106	## Audience Questions
107	- "..."
108
109	## Objections and Concerns
110	- Objection: ...
111	- Evidence: "..."
112	- Response angle: ...
113
114	## Buying Intent / Demand Signals
115	- "..."
116
117	## Exact Language to Reuse
118	- "..."
119	- "..."
120
121	## Content Ideas From Comments
122	1. ...
123	2. ...
124	```
125
126	## Quality Guardrails
127
128	- Label sample size and confidence.
129	- Separate one loud comment from a repeated pattern.
130	- Preserve exact quotes for useful language.
131	- Avoid claiming broad market sentiment from one post's comments.
132	- Call out moderation/platform bias when relevant.
133
134	## Common Pitfalls
135
136	- Do not flatten comments into generic sentiment. The value is in questions, objections, and exact wording.
137	- Do not include personally identifying details unless they are already public and necessary.
138	- Do not treat bot/spam comments as audience signal.
139	- Do not skip Reddit post context. For Reddit, read both the original post and comments.