Data & Analysis social-media-researchcompetitor-analysistrend-discoverycomment-miningad-library-analysisinfluencer-prospectingcontent-repurposing

Social Media Research Skills Pack

Ready-to-use AI agent skills for social media research: find outlier posts, mine comments, and analyze competitors.

FollowAgents review · FARS-2.1
Not recommended
27/ 100 5-point scale 1.4 / 5
1 2 3 4 5 6
1Trust0 / 29 · 0.0/5

Evidence: The repository contains only a README, no code or configuration, so permissions, user confirmation, data flow transparency, sensitive data handling, dependency security, external effects, rollback, and source attribution cannot be assessed. All criteria deducted due to lack of evidence.

2Reliability3 / 14 · 1.1/5

Evidence: README describes multiple skills and their collaboration, but no implementation details to verify self-consistency. Dependencies only mention ScrapeCreators API, but no availability guarantee. No failure messages or error handling described.

3Adaptability8 / 18 · 2.2/5

Evidence: README specifies target audience (AI agents) and multiple use cases (e.g., finding outlier posts, analyzing transcripts), but does not detail capability boundaries or trigger conditions. Environment fit only mentions support for multiple agents, but no specific configuration.

4Convention7 / 18 · 1.9/5

Evidence: README provides installation instructions and skill list, but no license, version history, or changelog. Naming stability and maintenance responsibility not clear. Known limitations only mention public data, but not detailed.

5Effectiveness7 / 13 · 2.7/5

Evidence: README describes outputs for each skill (e.g., tables, reports), but no actual examples or user feedback. Marginal value may be high, but cost-benefit not quantified.

6Verifiability2 / 8 · 1.3/5

Evidence: README claims skills are effective, but no verifiable tests or independent sources. Facts and inferences not clearly separated.

Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision 536725292cdc
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
Safety controls not found in source: least-privilege scoping, confirmation before acting, data-flow disclosure, sensitive-data handling, dependency security, disclosed external effects, rollback or recovery path, verifiable attribution
Before you use it
  • Repository contains only README, no actual code or configuration, functionality and security cannot be verified.
  • No license information provided, usage risk unknown.
  • Relies on external API, but no availability guarantee or error handling provided.
Review evidence [1]
See the full review method →

What does this agent do, and when should you use it?

ScrapeCreators/social-media-research-skills is a collection of practical AI agent skills for social media research, built on ScrapeCreators' data extraction API. The repository includes 13 workflow-oriented skills, each designed to turn raw social data into actionable business artifacts. Examples include 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, and content-repurposing. The skills rely on the scrapecreators-api skill as the underlying data layer, routing requests to the appropriate ScrapeCreators endpoints. Installation is straightforward via npx skills add, and the skills work with AI agents that support the Agent Skills specification, such as Claude Code, Cursor, OpenAI Codex, and GitHub Copilot. The design emphasizes workflow-first approaches, public-data-only constraints, cited outputs, and baseline-aware analysis to ensure outputs are not just raw JSON but useful reports and recommendations.

The repository provides pre-built workflow skills that guide an AI agent through specific social media research tasks. For instance, outlier-post-finder fetches recent posts from a creator and identifies those that outperform their baseline; transcript-intelligence analyzes video transcripts from multiple platforms and extracts summaries, hooks, and quotes; comment-mining scans comments for questions, objections, and purchase intent; competitor-social-research compares competitors' strategies on TikTok and Instagram; ad-library-teardown examines active Meta, Google, and LinkedIn ads; trend-discovery uncovers trending topics and formats; influencer-prospecting builds creator prospect lists; audience-research evaluates audience fit; social-listening-brief generates a multi-source brand or topic brief; product-demand-research validates product ideas; creator-profile-teardown analyzes why an account works; and content-repurposing transforms videos and posts into LinkedIn articles and newsletters. Each skill uses the scrapecreators-api skill to make API calls and outputs structured artifacts like CSV files, reports, and recommendation tables.

  1. A content creator wants to find which of their recent YouTube Shorts are outperforming their usual metrics and what patterns they share.
  2. A brand marketer needs to tear down a competitor's Facebook and Google ads to extract hooks, offers, and CTAs for their next campaign.
  3. A product manager wants to validate a new product idea by mining Reddit and social comments for pain points and exact user language.
  4. A growth hacker seeks to build a prospect list of influencers in a niche, evaluating their audience fit and engagement.
  5. A content team wants to repurpose a long webinar into LinkedIn posts, X threads, and newsletter articles using transcript analysis.

What are this agent's strengths and limitations?

Pros
  • Offers complete research workflows rather than simple endpoint routing, producing business-ready outputs.
  • All skills are integrated through a common data layer (scrapecreators-api), ensuring consistency and extensibility.
  • Emphasizes cited sources and baseline-aware analysis, increasing credibility and practical value.
  • Supports multiple major AI coding agents, including Claude Code, Cursor, Codex, and Gemini CLI, making it easy to adopt.
Limitations
  • Tied to ScrapeCreators' proprietary API, requiring a paid subscription or API key, creating vendor lock-in.
  • Limited to public data only; cannot access private or logged-in social media data, which may restrict some research scenarios.
  • Installation and execution require Node.js and network access to ScrapeCreators services, which may not be available in all environments.
  • The repository lacks a clear license, which may raise legal concerns for commercial use.

How do you install or deploy this agent?

Ensure Node.js is installed on your system. Then run the command: npx skills add ScrapeCreators/social-media-research-skills. This fetches the skills from GitHub and installs them. After installation, set your ScrapeCreators API key as an environment variable: export SCRAPECREATORS_API_KEY=sk_... You can obtain a key from scrapecreators.com.

How do you use this agent?

Once installed and configured, you can invoke the skills through natural language prompts in any supporting AI agent. For example, in Claude Code, you could say: "Find outlier posts for @starterstory on YouTube Shorts." The agent will trigger the outlier-post-finder skill, which uses scrapecreators-api to fetch data and return a table of outliers, patterns, and suggested hooks. Ensure network access is available so the agent can call the ScrapeCreators API.

FAQ

Is this skill pack free to use?
The skill pack is open-source, but all skills rely on the ScrapeCreators API, which requires an API key and may have costs. You can get a trial key on their website, but production use may require a paid plan.
Can I customize or extend these skills?
Yes, since it's a GitHub repository, you can fork and modify the skills as needed. However, the license is not specified, so check with the author for permissions. You'll also need to maintain your own fork.
What happens if I don't set up the API key?
The skills will fail to fetch data, as they all depend on ScrapeCreators API. You'll need to set the SCRAPECREATORS_API_KEY environment variable to a valid key before using the skills.
Which social media platforms are covered?
According to the README, the skills support TikTok, Instagram, YouTube, Reddit, X/Twitter, LinkedIn, Facebook, Threads, Bluesky, Pinterest, Rumble, and ad libraries (Meta, Google, LinkedIn). Specific coverage may vary by skill.

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