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Competitor Content Tracker — weekly competitive content digest — Claude Skill

A Claude Skill for Claude Code by Gooseworks — run /competitor-content-tracker in Claude·Updated

Compatible withClaude·ChatGPT·OpenClaw

Weekly digest of what competitors are publishing on blog, LinkedIn, and X

  • Tracks competitor blog, LinkedIn, and Twitter/X activity
  • Surfaces top posts by engagement per channel
  • Identifies trending themes across competitors
  • Maps content gaps you can own
  • Outputs weekly digest with action recommendations

Who this is for

What it does

Stay ahead of competitor content moves

Catch new content directions while they're still emerging instead of finding out months later.

Find content gaps to own

Identify topics multiple competitors are missing that match your audience.

Benchmark engagement

Understand what's actually working in your category before investing in new content formats.

How it works

1

Take competitor blog URLs and social handles as input

2

Scrape blog posts, LinkedIn posts, and X posts for the period

3

Identify top-performing content by engagement

4

Cross-analyze themes and gaps

5

Output a structured weekly digest

Metrics this improves

Engagement
Higher engagement by adopting topics and formats already validated in your category
Marketing

Works with

Want to use Competitor Content Tracker?

Choose how to get started.

Run in Claude Code
Free. Open source.

Install and run this skill locally on your computer.

1
Install Claude Code

Open a terminal on your computer and paste this command:

2
Install the skill

This downloads the skill with all its files to your computer:

Add -g at the end to make it available in all your projects.

3
Run it

Start Claude Code, then type the command:

then
View source on GitHub
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Competitor Content Tracker

Monitor competitor content activity across three channels — blog, LinkedIn, Twitter/X — and produce a consolidated digest highlighting what's new, what's getting traction, and where you have a content gap.

When to Use

  • "Track what [competitor] is publishing"
  • "Show me what my competitors posted this week"
  • "What topics are competitors winning on?"
  • "I want a weekly competitor content digest"

Phase 0: Intake

Competitors to Track

  1. List of competitor company names + blog URLs (e.g., https://clay.com/blog)
  2. LinkedIn profile URLs of competitor founders/CMOs to track (optional but high-value)
  3. Twitter/X handles of the competitors or their founders (optional)

Scope

  1. How far back? (default: 7 days for weekly digest, 30 days for first run)
  2. Any topics/keywords you care most about? (used to surface relevant posts first)

Output

  1. Format preference: full digest (everything) or highlights only (top 3-5 per competitor)?

Save config to clients/<client-name>/configs/competitor-content-tracker.json.

{
  "competitors": [
    {
      "name": "Clay",
      "blog_url": "https://clay.com/blog",
      "linkedin_profiles": ["https://www.linkedin.com/in/kareem-amin/"],
      "twitter_handles": ["@clay_hq", "@kareemamin"]
    }
  ],
  "days_back": 7,
  "keywords": ["GTM", "outbound", "AI agents", "growth"],
  "output_mode": "highlights"
}

Phase 1: Scrape Blog Content

Run blog-scraper for each competitor blog URL:

python3 skills/blog-scraper/scripts/scrape_blogs.py \
  --urls "<competitor_blog_url>" \
  --days <days_back> \
  --keywords "<keywords>" \
  --output summary

Collect: post title, publish date, URL, excerpt.

Phase 2: Scrape LinkedIn Posts

Run linkedin-profile-post-scraper for each tracked founder/executive LinkedIn URL:

python3 skills/linkedin-profile-post-scraper/scripts/scrape_linkedin_posts.py \
  --profiles "<linkedin_url_1>,<linkedin_url_2>" \
  --days <days_back> \
  --max-posts 20 \
  --output summary

Collect: post text preview, date, reactions, comments, post URL.

Phase 3: Scrape Twitter/X

Run twitter-scraper for each handle:

python3 skills/twitter-scraper/scripts/search_twitter.py \
  --query "from:<handle>" \
  --since <YYYY-MM-DD> \
  --until <YYYY-MM-DD> \
  --max-tweets 20 \
  --output summary

Collect: tweet text, date, likes, retweets, URL.

Phase 4: Analyze & Synthesize

After collecting raw data, synthesize across all channels:

For each competitor, identify:

  • New blog posts — titles, dates, topics
  • Top LinkedIn post — by engagement (reactions + comments), topic, key message
  • Top tweet — by likes, topic
  • Recurring themes — what topics did they post about most this period?
  • Content format patterns — are they doing listicles, opinion pieces, case studies?

Cross-competitor analysis:

  • Shared trending topics — what are multiple competitors writing about?
  • Coverage gaps — topics they're covering that you're not
  • Topics you own — where you're publishing and they're not
  • Engagement benchmarks — average likes/reactions across competitors (context for your own performance)

Phase 5: Output Format

Produce a structured markdown digest:

# Competitor Content Digest — Week of [DATE]

## Summary
- [N] new blog posts tracked across [N] competitors
- Top trending topic: [topic]
- Biggest content gap for you: [topic]

---

## [Competitor Name]

### Blog
- [Post Title] — [Date] — [URL]
  > [One-sentence summary]

### LinkedIn (top post)
> "[Post preview...]"
— [Author], [Date] | [Reactions] reactions, [Comments] comments
[URL]

### Twitter/X (top tweet)
> "[Tweet text]"
— [@handle], [Date] | [Likes] likes
[URL]

### Themes this week: [tag1], [tag2], [tag3]

---

## Content Gap Analysis

| Topic | Competitors covering | You covering |
|-------|---------------------|--------------|
| [topic] | Clay, Apollo | ❌ No |
| [topic] | Nobody | ✅ Yes |

## Recommended Actions
1. [Specific content opportunity to act on this week]
2. [Topic to consider writing a response/alternative take on]

Save digest to clients/<client-name>/intelligence/competitor-content-[YYYY-MM-DD].md.

Scheduling

This skill is designed to run weekly (Mondays recommended). Set up a cron job:

# Every Monday at 8am
0 8 * * 1 python3 run_skill.py competitor-content-tracker --client <client-name>

Cost

ComponentCost
Blog scraping (RSS mode)Free
LinkedIn post scraping~$0.05-0.20/profile (Apify)
Twitter scraping~$0.01-0.05 per run
Total per weekly run~$0.10-0.50 depending on scope

Tools Required

  • Apify API tokenAPIFY_API_TOKEN env var
  • Upstream skills: blog-scraper, linkedin-profile-post-scraper, twitter-scraper

Trigger Phrases

  • "Run competitor content tracker for [client]"
  • "What did my competitors publish this week?"
  • "Give me a competitor content digest"
  • "What's [competitor] writing about?"