$ loading_
Track and submit user-level token efficiency rankings with privacy-first controls.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "SigRank SignalAF — AI Operator Cascade & Leaderboard" MCP server from askskill: Run: claude mcp add 'io-github-sunrisesillneversee-sigrank-mcp' -- npx -y sigrank
Developers or researchers can use it to compare their own token efficiency across different tools. It focuses on measuring user operating performance rather than only the underlying models.
Command-line users can view and submit leaderboard results through a TUI. It suits people who prefer managing evaluation workflows in a terminal environment.
When individuals or teams want to share efficiency results while protecting privacy, they can use its privacy-first submission approach. It also mentions signed submission for managing results.
It is a token efficiency leaderboard focused on measuring user or operator performance rather than the models themselves. The description also mentions 20 tools, a TUI, signed submission, and a privacy-first approach.
The provided information indicates that it offers a TUI, meaning a terminal text interface. For installation details and runtime requirements, see the source repository.
It emphasizes ranking user or operator efficiency rather than scoring models alone. In other words, it focuses more on practical operating efficiency and token usage in real usage.
Route natural-language leaderboard queries to SigRank with rank, percentile, and delta metrics.
Track AI agent market intelligence, rankings, trust signals, and liveness.
Query reproducible crypto infrastructure benchmarks to evaluate onchain performance.
Measure impression-weighted SERP rank, projected clicks, and share of voice.
Check EVM or Solana token rug risk with a clear 0-10 verdict.
Perform efficient financial analysis, metric calculations, and transparent data interpretation.