competitor-intel
Competitor intelligence system. Track competitors across Reddit, Twitter/X, and LinkedIn. Run one-time deep research to create competitor profiles, then automate daily/weekly monitoring with consolidated reports and actionable signals. Reports delivered as markdown files and via email.
npx skills add majiayu000/claude-skill-registry --skill competitor-intel --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Competitor Intelligence Automated competitor monitoring and intelligence gathering system. **Important:** Before running any competitor intel commands, ask the user which competitors they want to track. Do not assume or hardcode competitor names. ## Quick Start ### One-Time: Research a New Competitor ```bash # Create a new competitor profile (agent-driven research) python3 competitor-intel/scripts/setup_competitor.py --name "CompanyName" --website https://example.com --slug companyname ``` Then run an agent research session to populate the profile. ### Daily: Reddit + Twitter Monitoring ```bash # Run daily signals collection (automated via cron) python3 competitor-intel/scripts/run_daily.py # Or for a specific competitor python3 competitor-intel/scripts/run_daily.py --competitor <competitor-slug> ``` ### Weekly: Deep Dive + LinkedIn ```bash # Run weekly deep dive (Monday mornings) python3 competitor-intel/scripts/run_weekly.py ``` ### Generate Report ```bash # Generate daily or weekly report python3 competitor-intel/scripts/generate_report.py --type daily --date 2026-02-21 python3 competitor-intel/scripts/generate_report.py --type weekly --date 2026-02-21 ``` ## Data Structure -
- Quick Start
- One-Time: Research a New Competitor
- Daily: Reddit + Twitter Monitoring
- Weekly: Deep Dive + LinkedIn
- Generate Report
- Data Structure
- Tracked Competitors
- Automation
- Dependencies
Create a new competitor profile (agent-driven research) python3 competitor-intel/scripts/setup_competitor.py --name "CompanyName" --website https://example.com --slug companyname Run daily signals collection (automated via cron) python3 competitor-intel/scripts/run_daily.py Or for a specific competitor python3 competitor-intel/scripts/run_daily.py --competitor <competitor-slug> Run weekly deep dive (Monday mornings) python3 competitor-intel/scripts/run_weekly.py Generate daily or weekly report python3 competitor-intel/scripts/generate_report.py --type daily --date 2026-02-21
What does the competitor-intel skill do?
Competitor intelligence system. Track competitors across Reddit, Twitter/X, and LinkedIn. Run one-time deep research to create competitor profiles, then automate daily/weekly monitoring with consolidated reports and actionable signals. Reports delivered as markdown files and via email.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill competitor-intel --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.