Competitor Content Tracker Agent Skill
> Monitor competitor content across blogs, LinkedIn, and Twitter/X on a recurring basis. Surfaces new posts, trending topics, and content gaps you can own. Chains blog-feed-monitor, linkedin-profile-post-scraper, and twitter-mention-tracker. Use when you want a weekly digest of what competitors are publishing and which topics are generating engagement.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/gooseworks-ai/goose-skills --skill competitor-content-trackerWhat comes with it
402 bytes besides the instructionThe instruction itself
17 sections, as written by the authorCompetitor 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
- List of competitor company names + blog URLs (e.g.,
https://clay.com/blog) - LinkedIn profile URLs of competitor founders/CMOs to track (optional but high-value)
- Twitter/X handles of the competitors or their founders (optional)
Scope
- How far back? (default: 7 days for weekly digest, 30 days for first run)
- Any topics/keywords you care most about? (used to surface relevant posts first)
Output
- 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-feed-monitor for each competitor blog URL:
python3 skills/capabilities/blog-feed-monitor/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/capabilities/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-mention-tracker for each handle:
python3 skills/capabilities/twitter-mention-tracker/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
| Component | Cost |
|-----------|------|
| 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 access — via Gooseworks proxy by default (no key needed); set
APIFY_API_TOKENto BYO Apify - Upstream skills:
blog-feed-monitor,linkedin-profile-post-scraper,twitter-mention-tracker
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?"
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How to use it
Take gooseworks-ai/competitor-content-tracker from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.