Track and compare competitor content activity
competitor-content-trackerskillsetup L3★76
stevehuang0115/crewly ↗Causal-lift measurements
competitive-intelligence+10pp vs no-skill baselinewith-skill 69% · baseline 59%
Measured by running the task with and without this artifact, K=5, graded by deterministic checks — no LLM judging.
What it does
Track and compare competitor content activity
Best for
Product strategy when you need quantified evidence of competitor activity (release velocity, topic focus, engagement trends) to inform roadmap priorities.
Inputs
- · competitor names (CrewAI, n8n, Relevance AI, etc.)
- · source types (blog, Twitter, GitHub, PyPI, YouTube)
- · date range for content collection
- · engagement metrics (likes, retweets, replies)
Outputs
- · structured content inventory (competitor, sourceType, items array)
- · comparison report across competitors by period
- · trend analysis (topics, frequency, engagement patterns)
- · content activity timeline
Requires
- · Browser automation (Playwright)
- · Web scraping (for GitHub releases, blog dates)
- · bash execute.sh script (data storage and queries)
Preconditions
- · Competitor list defined
- · execute.sh script configured with project path
- · Browser access to competitor sites
Failure modes
- · GitHub releases/changelog format changes → scraper breaks
- · Twitter/X API changes → engagement metrics unreliable
- · Blog dates missing in page metadata → extraction fails
- · Rate limiting on competitor sites → incomplete data collection
Trust signals
- · Competitor-specific scraping strategies (CrewAI PyPI + GitHub, n8n community + security tags)
- · Content item schema with 7 fields (title, URL, date, description, engagement, type, tags)
- · Data actions: save, list, latest, compare (not just one-off reads)
- · Example save commands showing full JSON structure