social-media-research-skills

Social Media Research Skills for AI Agents

Practical AI agent skills for social media research, powered by ScrapeCreators.

These skills help agents find outlier posts, mine comments, summarize transcripts, tear down competitors, analyze ad libraries, and turn public social data into useful business artifacts.

This is not just endpoint routing. The goal is to give your AI agent complete research workflows it can run across TikTok, Instagram, YouTube, Reddit, X/Twitter, LinkedIn, Facebook, Threads, Bluesky, Pinterest, Rumble, ad libraries, and more.

Install

npx skills add ScrapeCreators/social-media-research-skills

Works with Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Windsurf, VS Code, and other agents that support the Agent Skills spec.

Setup

Set your ScrapeCreators API key:

export SCRAPECREATORS_API_KEY=sk_...

Get a key at scrapecreators.com.

Available Skills

Skill	Use it when you want to...	Output
outlier-post-finder	Find posts, reels, shorts, tweets, or videos that beat a creator's baseline	Outlier table, repeatable patterns, hooks to steal
transcript-intelligence	Analyze video transcripts from TikTok, Instagram, YouTube, Facebook, X, LinkedIn, Rumble, or Reddit	Summary, hooks, claims, quotes, content atoms
comment-mining	Mine comments for questions, objections, pain points, product ideas, and audience language	VOC report, themes, quotes, content ideas
competitor-social-research	Compare competitors' social strategy and find what is working	Competitor brief, content pillars, gaps, recommendations
ad-library-teardown	Analyze active Meta, Google, and LinkedIn ads	Messaging angles, hooks, CTAs, offers, test ideas
trend-discovery	Find trending topics, hashtags, sounds, posts, and short-form formats in a niche	Trend brief, evidence table, suggested content angles
influencer-prospecting	Build creator or influencer prospect lists from public social data	Prospect CSV/table, fit score, outreach notes
audience-research	Evaluate creator or brand audience fit from public profile and demographic signals	Audience-fit report, market/country notes, confidence labels
social-listening-brief	Research what people are saying about a brand, topic, product category, or niche	Multi-source brief, themes, cited examples, sentiment caveats
product-demand-research	Validate product ideas and find pain points from social posts, comments, and Reddit	Demand signals, pains, objections, exact language, ideas
creator-profile-teardown	Analyze why a creator or brand account works and what to copy	Positioning teardown, content pillars, outliers, playbook
content-repurposing	Turn social videos, transcripts, and posts into reusable content assets	LinkedIn posts, X threads, scripts, newsletter/blog ideas
scrapecreators-api	Route a raw scraping/fetching request to the right ScrapeCreators endpoint	API calls, endpoint references, pagination guidance

Example Prompts

Find the outlier posts for @starterstory on YouTube Shorts from the latest page of videos.

Analyze the transcripts from these 12 TikToks and pull out the best hooks, claims, and reusable content angles.

Mine the comments on this viral Instagram Reel. I want objections, questions, buying intent, and exact audience language.

Compare these five brands on TikTok and Instagram. What formats and topics are working for each one?

Tear down the active Facebook, Google, and LinkedIn ads for this competitor. Give me hooks, offers, CTAs, and what to test.

How the Skills Work Together

scrapecreators-api
        │
        ▼
social research workflows
 ├─ outlier-post-finder
 ├─ transcript-intelligence
 ├─ comment-mining
 ├─ competitor-social-research
 ├─ ad-library-teardown
 ├─ trend-discovery
 ├─ influencer-prospecting
 ├─ audience-research
 ├─ social-listening-brief
 ├─ product-demand-research
 ├─ creator-profile-teardown
 └─ content-repurposing

The workflow skills should use scrapecreators-api as the data layer when they need endpoint details. Each workflow produces a useful artifact, not just raw JSON.

Design Principles

1. Workflow-first, API-second — users ask for a business outcome, not an endpoint.
2. Public-data only — ScrapeCreators extracts public social data. Do not promise logged-in/private data.
3. Cited outputs — include source URLs for posts, videos, ads, and comments whenever possible.
4. Baseline-aware analysis — judge performance against a creator's own normal performance, not only raw vanity metrics.
5. Exact language matters — preserve useful comments, hooks, captions, and transcript quotes verbatim.
6. Keep outputs actionable — end with patterns, recommendations, test ideas, or a CSV when useful.

Links

• ScrapeCreators
• API Documentation
• MCP Integration
• Agent Skill Docs