| name | youtube-rl-tracker |
| description | Track YouTube video performance for "poor man's reinforcement learning" - learn what thumbnails, titles, and hooks work |
| license | MIT |
| compatibility | opencode |
| metadata | {"service":"notion, youtube","category":"content"} |
What I Do
Track YouTube video performance to discover patterns in what works. This is "poor man's reinforcement learning" - manually logging outcomes to improve over time.
The RL Loop
1. PUBLISH -> Upload video with hypothesis (thumbnail style, title hook, topic)
2. WAIT -> Let it run for 48-72 hours
3. LOG -> Record in Notion with views, CTR, retention
4. ANALYZE -> Compare winners vs losers
5. REPEAT -> Apply learnings to next video
Key Insight from First Data Point
Video 1: "Using AI agents to pay bills and send invoices"
- 8 views in 1 day
- Plain talking head thumbnail
- Generic title
Video 2: "Paying My Contractor Through Claude | AI-Powered Finance"
- 133 views in 5 days (16x better!)
- Thumbnail shows: Face + Product UI overlay + Text "I Let AI Pay My Bills"
- Title has: Specific action + Brand name (Claude) + Category tag