Competitor Monitoring System
Set up and run ongoing competitive intelligence monitoring for a client. Tracks competitor content, ads, reviews, social, and product moves.
by Athina AInpx gooseworks install --claude # Then in your agent: /gooseworks <prompt> --skill competitor-monitoring-system
Competitor Monitoring System
Set up ongoing competitive intelligence for a client. Monitor competitor content, ads, reviews, social presence, and product moves. Produce regular intelligence reports.
When to Use
- "Set up competitor monitoring for [client]"
- "Track what [competitors] are doing"
- "Monitor [competitor] content and ads"
Prerequisites
- List of competitors to track (typically 3-7)
- Client context with competitive positioning
- Competitor founder/executive LinkedIn profiles (for social monitoring)
Setup Steps
1. Define Competitor Watchlist
Create a competitor tracking file: clients/<client-name>/intelligence/competitor-watchlist.md
For each competitor, document:
- Company name and URL
- Key products/features
- Founder/exec LinkedIn profiles
- Known content channels (blog URL, YouTube, podcast)
- Review profiles (G2, Capterra URLs)
- Ad library pages (Meta, Google)
2. Initial Competitive Baseline
Run the full competitor-intel composite for each competitor to establish a baseline:
Skill: competitor-intel (chains reddit + twitter + linkedin + blog + review scrapers)
Plus:
- Skill: google-ad-scraper — Scrape their current Google ads
- Method: Use
web_searchagainst Meta Ad Library (facebook.com/ads/library) for Meta ad research - Skill: review-site-scraper — Pull latest G2/Capterra/Trustpilot reviews
Output: clients/<client-name>/intelligence/competitor-baseline.md
3. Configure Monitoring Cadence
| What to Monitor | Frequency | Skill | What to Look For |
|---|---|---|---|
| Blog/content output | Weekly | blog-feed-monitor | New posts, topic shifts, SEO attacks |
| Social media posts | Weekly | linkedin-profile-post-scraper + twitter-mention-tracker | Messaging changes, product announcements, engagement patterns |
| Reddit/HN mentions | Weekly | reddit-post-finder + hacker-news-scraper | User sentiment, complaints, praise, feature requests |
| Ad creative changes | Bi-weekly | google-ad-scraper + web_search (Meta Ad Library) | New campaigns, messaging shifts, spend changes |
| Review sentiment | Monthly | review-site-scraper | New reviews, rating trends, common complaints |
4. Run Monitoring
Each monitoring cycle:
- Run the relevant scrapers for the cycle type
- Compare new data against the baseline/previous cycle
- Flag significant changes:
- New product features or pricing changes
- New content targeting our client's keywords
- Negative review trends (poaching opportunity)
- New ad campaigns (messaging intelligence)
- Founder/exec public statements about strategy
5. Produce Intelligence Report
After each cycle, produce a brief intelligence summary:
# Competitor Intelligence — [Client] — Week of [Date]
## Key Changes
- [Competitor A] published 3 new blog posts targeting "[keyword]"
- [Competitor B] launched new Meta ad campaign focused on [theme]
- [Competitor C] received 5 negative G2 reviews about [issue]
## Recommended Actions
- Publish response content for [Competitor A]'s keyword attack
- Create comparison page addressing [Competitor B]'s new messaging
- Target [Competitor C]'s unhappy customers with migration content
## Detailed Findings
[Per-competitor breakdown]Output: clients/<client-name>/intelligence/competitor-reports/[date].md
Ongoing Cadence
- Weekly: Content + social monitoring, brief report
- Bi-weekly: Ad monitoring
- Monthly: Full review scrape + comprehensive report
- Quarterly: Re-run full competitor-intel baseline, update watchlist
Human Checkpoints
- After setup: Review competitor watchlist and monitoring plan
- After each report: Review recommended actions before executing
What's included
Meta Ads Analyzer
Diagnose Meta Ads campaign performance using Meta's actual system mechanics — Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue — and produce structured, testable recommendations that avoid judging segments by average CPA instead of marginal efficiency.
Meta Ad Policy Checker
Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.
Ad Lead Quality Analyzer
For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.