whoburnedmore

Spotify Wrapped for Claude, Codex with a public leaderboard

Vercel DayDeveloper ToolsArtificial IntelligenceOpen Source

▲ 80 votes8 commentsLaunched Jun 16, 2026

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Daily #35Weekly #52

Run `npx whoburnedmore` and get an instant dashboard of your AI coding usage - tokens, cost, tool usages, mcps, skill & all else across Claude Code, Codex, Cursor, Open code and 12 more in a single place. Then land on a live public leaderboard and compare it with others. Free and open source.

AI Analysis

📝 Summary

whoburnedmore is a free, open-source CLI tool that delivers a Spotify Wrapped-style instant dashboard for AI coding usage. Running `npx whoburnedmore` aggregates and visualizes tokens, costs, tool usages, MCPs, skills, and more across Claude, Codex, Cursor, OpenAI, and 12+ other platforms in one place. It also features a live public leaderboard for community comparison. It addresses the core pain of fragmented, hard-to-track AI tool consumption and spend across multiple services, offering unified insights, optimization opportunities, and gamified engagement for developers.

📈 Market Timing

2025-2026 sees massive mainstream adoption of AI coding assistants with rising concerns over costs, efficiency, and usage transparency. Developer demand for analytics, gamification, and community features is surging amid maturing LLM tech and economic pressure to optimize AI spend. The fun Wrapped format and public leaderboard fit perfectly into current open-source and social coding trends. Excellent Timing.

✅ Feasibility

High. The npx-based CLI indicates low technical barriers using JavaScript and existing APIs or local logs for data aggregation. Open-source model keeps development and maintenance costs minimal. Leaderboard hosting via Vercel is low-cost and scalable. Limited compliance risks for usage analytics; strong scalability for growing user base. High feasibility with proven execution.

🎯 Target Market

Primary segments: Software developers, AI engineers, full-stack programmers, and indie hackers (ages 22-45) heavily using AI coding tools. Industries: Tech, software development, startups. Geographic: Global with concentration in US, Europe, China, India. TAM for dev tools ~$60B, SAM for AI productivity ~$8B, SOM for usage analytics ~$200M+. Pain points: Scattered usage data and no peer benchmarks. Willingness to pay: Moderate-high for premium insights; free tier drives virality.

⚔️ Competition

Low. Direct competitors: 1. WakaTime (wakatime.com) - general coding analytics; 2. CodeTime by vsCode (codetime.dev); 3. Anthropic Usage Console; 4. OpenAI Usage Dashboard; 5. Cursor built-in usage metrics. Advantages: Multi-platform unification (15+ tools), engaging Wrapped presentation, public leaderboard, completely free/open-source. Disadvantages: Potentially shallower per-tool depth than official dashboards and public data sharing may raise privacy questions for some users.

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