SigRank — Measure AI efficiency with a privacy focused…

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About this project

SigRank offers a unique, privacy-preserving leaderboard that evaluates AI operator efficiency. Unlike conventional platforms that reward volume, SigRank emphasizes a structured approach, allowing users to assess their performance based on token cascade efficiency. Join the community of AI operators aiming for efficiency without compromising privacy.

SigRank: Privacy-Preserving AI Operator Leaderboard

SigRank is a revolutionary leaderboard dedicated to assessing the efficiency of AI operators by measuring their token cascade efficiency. By focusing on how effectively reusable signals are created from each unit of input rather than merely the volume of tokens consumed, SigRank sets a new standard for AI performance evaluation.

Key Features

Efficiency-Oriented Ranking: Instead of rewarding the raw volume of actions, SigRank measures how well AI operators utilize resources. The ranking is based on the formula:

Υ = (cache_read × output) / input²

Anonymity and Claims: The leaderboard operates on an anonymous basis by default, allowing operators to claim their profiles while maintaining privacy.
Accessible Scoring System: Operators can easily check their projected rank within 60 seconds by providing usage statistics at signalaf.com/score.

User Experience

Users can quickly visualize their efficiency scores without needing to navigate complex installations. The command-line interface (CLI) enables seamless interaction, allowing individuals to derive their cascade from local AI session logs and submit their verified runs to the leaderboard. Example commands include:

npm install -g sigrank  # initializes SigRank CLI tools  
sigrank enroll            # connect using a code from settings  
sigrank submit            # publish verified runs to the board  ```  
A feature that ensures privacy is the `sigrank submit --dry-run` command, which allows users to view the exact payload that would be sent without actually submitting it.  

### Development Insights  
This repository contains the implementation of the Next.js application that fuels [signalaf.com](https://signalaf.com), including essential features such as the public leaderboard, operator profiles, and the scoring engine. It utilizes a modern tech stack, incorporating:  
- **Next.js 15** for streamlined app development  
- **React 19** for rich user interfaces  
- **TypeScript** for maintainable and scalable code  
- **Supabase** as the backend for data management  

### Community and Collaboration  
Developers interested in contributing to SigRank can access detailed guidelines and the full development environment setup in the README. The community is encouraged to participate through [contributing](https://github.com/SunrisesIllNeverSee/sigrank-app/blob/main/./.github/CONTRIBUTING.md) and to stay informed via the [changelog](https://github.com/SunrisesIllNeverSee/sigrank-app/blob/main/./CHANGELOG.md).  

For a comprehensive exploration of features and updates, visit [signalaf.com](https://signalaf.com). SigRank is setting a new trajectory in how AI operators are evaluated, prioritizing efficiency over sheer volume.