competitor-social-research

competitor-social-research is a skill for Claude Code from ScrapeCreators/social-media-research-skills. It costs 49 tokens per session (990 once invoked), scanned A, original, MIT.

A workflow for researching competitors’ public social-media activity across platforms such as TikTok, Instagram, YouTube, LinkedIn, Facebook, X, and Threads. It compares profiles, recent posts, performance patterns, and content topics.

In plain words
What is it for?
Benchmark posting frequency, formats, topics, and engagement; compare competitors; find unusually successful posts; analyze videos and comments; and create a practical social strategy brief.
Why use it?
It brings scattered public social data into a comparable view and helps reveal which posts stand out for each competitor. It can also show topics or formats that competitors are not covering.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: built for openclaw.

Part of the social-media-research-skills plugin — 13 skills shipped together

Good fit Benchmark posting frequency, formats, topics, and engagement; compare competitors; find unusually successful posts; analyze videos and comments; and create a practical social strategy brief.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/scrapecreators/social-media-research-skills/competitor-social-research
About the project

Social Media Research Skills is a collection of workflows that let AI coding agents research public social-media data across platforms such as TikTok, Instagram, YouTube, Reddit, and LinkedIn. Marketers and researchers use it to find unusually successful posts, mine comments, study competitors, analyze ads, and extract trends into business outputs. The catalogue skills and plugin package these workflows for supported AI agents.

ScrapeCreators/social-media-research-skills · 2,234 stars · on GitHub · scrapecreators.com

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ScrapeCreators/social-media-research-skills --skill competitor-social-research
Clone the repo
git clone --depth 1 https://github.com/ScrapeCreators/social-media-research-skills

Made for: Claude Code.

Or install social-media-research-skills, the plugin that ships this one along with the rest of its 13 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for competitor-social-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/scrapecreators/social-media-research-skills/competitor-social-research/github.svg)](https://agentmods.dev/skills/scrapecreators/social-media-research-skills/competitor-social-research)
Your own site
<a href="https://agentmods.dev/skills/scrapecreators/social-media-research-skills/competitor-social-research"><img src="https://agentmods.dev/badge/skills/scrapecreators/social-media-research-skills/competitor-social-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for competitor-social-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/scrapecreators/social-media-research-skills/competitor-social-research"><img src="https://agentmods.dev/badge/skills/scrapecreators/social-media-research-skills/competitor-social-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 990 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 23 Jun 2026
  • Snyk warn 23 Jun 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00990
Opus 5 $0.00024 $0.00495
Sonnet 5 $0.00010 $0.00198
Haiku 4.5 $0.00005 $0.00099

Measured 12d ago against content hash 3a5179df374d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

competitor-social-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/competitor-social-research/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Competitor Social Research

Overview

Analyze what competitors are doing on social and what appears to be working. This skill combines profile data, recent posts, outlier analysis, transcripts, and optionally comments to produce a practical competitor brief.

When to Use

Use this skill when the user asks to:

  • compare competitors on TikTok, Instagram, YouTube, LinkedIn, Facebook, X, Threads, or other social platforms
  • find what content is working in a niche
  • benchmark posting frequency, formats, topics, and engagement
  • identify content gaps or opportunities
  • build a social strategy from competitor research

Workflow

  1. Define competitors and platforms

    • Use provided handles/URLs.
    • If only company names are provided, search profiles first and confirm likely matches when ambiguity matters.
  2. Fetch profile snapshots

    • Followers/subscribers
    • Bio/positioning
    • Links
    • Verification/public metadata
  3. Fetch recent content

    • Pull comparable recent windows per competitor.
    • Track source URLs, dates, captions, formats, and metrics.
  4. Find outliers per competitor

    • Use each account's own median baseline.
    • Do not compare raw views between a huge brand and a small brand without context.
  5. Analyze content strategy

    • Content pillars
    • Formats
    • Hook styles
    • Posting cadence
    • Offers/CTAs
    • Use of founder/creator personality
    • Community/comment patterns
  6. Find gaps and opportunities Look for:

    • topics competitors avoid
    • formats that overperform but few competitors use
    • unanswered audience questions
    • weak hooks or repetitive content
    • platform whitespace

Useful ScrapeCreators Endpoints

Use the relevant profile/feed/detail/transcript/comment endpoints from scrapecreators-api. Common routes include:

  • TikTok: /v1/tiktok/profile, /v3/tiktok/profile/videos
  • Instagram: /v1/instagram/profile, /v2/instagram/user/posts, /v1/instagram/user/reels
  • YouTube: /v1/youtube/channel, /v1/youtube/channel-videos, /v1/youtube/channel/shorts
  • LinkedIn: /v1/linkedin/company, /v1/linkedin/company/posts
  • Facebook: /v1/facebook/profile, /v1/facebook/profile/posts, /v1/facebook/profile/reels
  • X/Twitter: /v1/twitter/profile, /v1/twitter/user-tweets
  • Threads: /v1/threads/profile, /v1/threads/user/posts
  • Bluesky: /v1/bluesky/profile, /v1/bluesky/user/posts

Read the full file on GitHub · 133 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 133 lines · 49 tokens per session scan A 3a5179df374d

Subscribe to this mod's changes

competitor-social-research is a skill published in the GitHub repository ScrapeCreators/social-media-research-skills (2,234 stars, last pushed 16d ago), licensed MIT. It adds 49 tokens to every session and 990 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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