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Token efficiency vs time tracking — Yield vs hours
| Feature | SigRank | WakaTime |
|---|---|---|
| What it tracks | AI token usage — the cascade | Coding time — hours, languages, editors |
| Headline metric | Yield (Υ) — token-cascade efficiency | Hours coded per day/week |
| What it tells you | How efficiently you use AI | How long you coded |
| AI-specific? | Yes — designed for AI coding sessions | No — general coding time tracker |
| Leaderboard | Yes — ranked by Yield | Yes — ranked by hours coded |
| Privacy | Token counts only — never prompt content | File names, project names, time stamps |
WakaTime tells you how many hours you coded. That's useful for time management. But in the AI era, time spent doesn't correlate with value produced. An operator who uses AI efficiently can produce in 2 hours what used to take 8.
SigRank measures the quality of your AI usage, not the quantity of your time. Yield (Υ) tells you whether your AI sessions are compounding signal or burning tokens. Two operators can code for the same number of hours — the one with higher Yield is getting more value from AI.
WakaTime tracks how many hours you code — time, languages, editors. SigRank measures how efficiently you use AI tokens with Yield. Time spent doesn't equal value produced; an AI user who uses Claude or Cursor efficiently can produce in 2 hours what used to take 8.
No — they track different things. WakaTime tracks coding time for time management; SigRank measures AI token efficiency for skill ranking. A developer can use WakaTime for hours and SigRank for how well they use AI during those hours.
Yield (Υ) = (cache_read × output) / input² — token-cascade efficiency from real sessions. Works across Claude, GPT, Gemini, Cursor, Copilot, and any AI coding tool.
Visit signalaf.com/score to enroll and submit your token telemetry. SigRank will compute your Yield, your rank, and your operator class. Token counts only — never prompt content, never code.
Efficiency > hours.
Check my Yield