Influencer Discovery
tigerless-labs/influencer-discovery
Find the bloggers/creators who can help promote your work, capture their contact info, and append them to the target sheet in Google Sheets.
A skill your agent uses when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or…
Install Comment Mining
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ScrapeCreators/social-media-research-skills comment-mining --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/comment-mining .claude/skills/comment-mining && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .claude/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-miningType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ScrapeCreators/social-media-research-skills comment-mining --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/comment-mining .agents/skills/comment-mining && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .agents/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ScrapeCreators/social-media-research-skills comment-mining --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/comment-mining .cursor/skills/comment-mining && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .cursor/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ScrapeCreators/social-media-research-skills.git --path skills/comment-mining--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ScrapeCreators/social-media-research-skills comment-mining --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/comment-mining .gemini/skills/comment-mining && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .gemini/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ScrapeCreators/social-media-research-skills comment-miningInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/comment-mining .github/skills/comment-mining && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .github/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ScrapeCreators/social-media-research-skills comment-mining --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/comment-mining .opencode/skills/comment-mining && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "comment-mining" agent skill from https://github.com/ScrapeCreators/social-media-research-skills/tree/main/skills/comment-mining into .opencode/skills/comment-mining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "comment-mining", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
comment-mining- GitHub stars
- 3.3k
- Token cost
- ~1k tokens
- SKILL.md length
- 327 words
- Files
- 1
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or…
- Works in 5 steps: Fetch comments → Clean lightly → Classify each useful comment → …
- The user wants to mine comments and replies for audience reactions
- SKILL.md covers Overview, When to Use, Comment Sources and Workflow, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Comment Mining is an agent skill from ScrapeCreators/social-media-research-skills. 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.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Marketing & SEO, covering Market research and Social media posts. It works with YouTube, TikTok, Instagram and Reddit. The repository describes itself as: AI agent skills for social media research. Outlier posts, comment mining, competitor teardowns, ad libraries & trends across TikTok, Instagram, YouTube, Reddit, X, LinkedIn &… The licence is MIT.
When your agent uses it
- The user wants to mine comments and replies for audience reactions
- Customer language
- Voice-of-customer insights from public social posts and videos
Example prompts
- “/comment-mining”
Requirements
- A credential in SCRAPECREATORS_API_KEY
- Pre-approved tools (allowed-tools): Bash, Read, Write, WebFetch
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Fetch comments
- Clean lightly
- Classify each useful comment
- Cluster themes
- Turn insights into actions
What it can do on your machine
Read from SKILL.md and the folder at commit 64ba7b4. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
BashReadWriteWebFetch
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Comment Mining loads about 1k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 327 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash, Read, Write, WebFetch
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from ScrapeCreators/social-media-research-skills at commit 64ba7b4, republished under its MIT licence (© ScrapeCreators). 327 words, ~1,017 tokens.
Download SKILL.mdSave it as
.claude/skills/comment-mining/SKILL.md (or your agent's skills folder).- 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
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
- 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.
© ScrapeCreators, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/comment-mining of ScrapeCreators/social-media-research-skills.
Open the folder on GitHubat commit 64ba7b4
Compare with similar skills
Comment Mining next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Comment Mining this skillScrapeCreators/social-media-research-skills | 3.3k | — | ~1k | Automated safety check: Notes | MIT | |
| Influencer Discoverytigerless-labs/influencer-discovery | 211 | — | ~2.5k | Automated safety check: Notes | None | |
| Google Social Media Finderbrowser-act/skills | 6.1k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Bulkpublish Social Schedulingdavepoon/buildwithclaude | 3.6k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Social SEOsocial-media-skills/skills | 116 | — | ~2k | Automated safety check: Pass | MIT | |
| Content Opportunity Briefunifapi-agent/agents | 586 | — | ~2.3k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Comment Mining
What does Comment Mining do?
A skill your agent uses when the user wants to mine comments and replies for audience reactions, customer language, questions, objections, complaints, product ideas, buying intent, sentiment, or…. Comment Mining is an agent skill from ScrapeCreators/social-media-research-skills. 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.
When should I use Comment Mining?
Comment Mining fits situations like: the user wants to mine comments and replies for audience reactions; customer language; voice-of-customer insights from public social posts and videos.
How do I install Comment Mining in Claude Code?
Run `npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a claude-code`. Or copy the skill folder (skills/comment-mining in ScrapeCreators/social-media-research-skills) into .claude/skills/comment-mining in your project. Claude Code loads it when a task matches its description.
How do I install Comment Mining in Codex?
Run `npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a codex`. Or copy the skill folder (skills/comment-mining in ScrapeCreators/social-media-research-skills) into .agents/skills/comment-mining in your project. Codex loads it when a task matches its description.
Can I use Comment Mining in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ScrapeCreators/social-media-research-skills --skill comment-mining -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/comment-mining, .gemini/skills/comment-mining, .github/skills/comment-mining and .opencode/skills/comment-mining in your project.
What does Comment Mining need to run?
SKILL.md names no scripts, command-line tools or credentials: Comment Mining is instructions for the agent only. Our summary lists: A credential in SCRAPECREATORS_API_KEY. Its frontmatter pre-approves these tools: Bash, Read, Write, WebFetch.
Does Comment Mining access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Comment Mining safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Comment Mining use?
Comment Mining is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Comment Mining use?
About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Comment Mining?
Skills that share tags, products or a category with Comment Mining: Influencer Discovery (tigerless-labs/influencer-discovery, 211 stars), Google Social Media Finder (browser-act/skills, 6.1k stars), Bulkpublish Social Scheduling (davepoon/buildwithclaude, 3.6k stars) and Social SEO (social-media-skills/skills, 116 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Comment Mining?
ScrapeCreators (a GitHub organization) maintains it in ScrapeCreators/social-media-research-skills, which has 3,258 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on August 26, 2026.
Source: ScrapeCreators/social-media-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.