SigRank — AI Operator Benchmarking
com.signalaf/sigrankSigRank benchmark MCP: cascade metrics, leaderboard, operator profiles, simulation, diagnostics.
Score: 100/100
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Tools · 16
Calculate SigRank cascade metrics from four non-negative token counts without submitting data. Returns Yield, Leverage, Velocity, SNR, and 10xDEV. No data is persisted.
Build a tteop/0.1-draft portable operator record from available token telemetry. Input and output are required; unavailable cache telemetry remains null. Computes only the five-metric portable core th…
Read the current public SigRank operator leaderboard. Returns ranked operators with Yield, Leverage, class tier, and display name. Profile text fields (display_name, codename, handle, bio) are user-su…
Read one public operator profile by codename. Returns class tier, rank, percentile, Yield, Leverage, Velocity, and SNR. Profile text fields (display_name, codename, handle, bio) are user-supplied, unt…
Prescriptive 'what if' tool — takes your current 4 token pillars and proposed changes, runs the cascade on both, returns the exact Υ Yield delta, class change, and per-metric diffs. Test proposed pill…
Analyzes your token cascade and diagnoses where you're leaking efficiency. Takes 4 token pillars and produces a ranked list of efficiency leaks with severity (critical/warning/info), findings, recomme…
Generates ranked, simulated improvement suggestions for your token cascade. Takes 4 token pillars, tests multiple strategies (increase cache reads, reduce input, increase output, optimize cache creati…
Runs the full self-improvement cycle in one call: (1) computes your current cascade from 4 token pillars, (2) diagnoses efficiency leaks, (3) generates ranked improvement suggestions, (4) simulates th…
Score up to 4 time windows (7d, 30d, 90d, all-time) in one call. Each window is scored independently with the full cascade (Υ, SNR, Leverage, Velocity, 10xDEV, class). Omit windows you don't have — pa…
Answers 'How good am I?' — benchmarks your token cascade against the live field. Takes 4 token pillars (or a codename), computes your cascade, then compares against the live leaderboard: percentile, r…
Answers 'What would it take to reach a target rank?' — takes your current 4 token pillars and a target percentile (e.g. 90 for top 10%), then simulates the smallest metric changes needed to reach that…
Answers 'What specifically separates operator A from operator B?' — not just 'A has more Yield', but the primary cause, secondary cause, and offsetting weakness. Takes two codenames or two sets of pil…
Finds unusual operators, metric relationships, and outliers in the live leaderboard — without user prompting. Returns: highest velocity among below-median leverage operators, only top-50 operator with…
Finds operators whose operating signature most resembles yours. Takes 4 pillars or a codename, computes your signature, then searches the live leaderboard for the nearest neighbors by signature distan…
Creates a 'YOU vs FIELD vs TOP 10% vs TOP 1%' comparison table for your cascade metrics. Takes 4 pillars or a codename, fetches the live leaderboard, and returns your metrics alongside field median, t…
Computes a normalized operating signature from 4 token pillars or a codename. Returns a signature code, a legacy six-label signature_label, dominant trait, and closest comparable operators from the li…
Resources · 8
Version, scope, canonical URLs, portable core, and explicit compatibility exclusions for TTEOP (Token Telemetry Evaluation Operator Protocol)
sigrank://standard
Canonical JSON Schema for a portable sigrank/0.1-draft operator record
sigrank://standard/schema
How SignalAF implements the SigRank portable core alongside optional reference and product layers
sigrank://methodology
Definitions of the five-metric SigRank portable core and the boundary around optional SignalAF extensions
sigrank://metrics
AI platforms tracked by SigRank
sigrank://platforms
The five SigRank portable-core formulas plus clearly separated SignalAF reference and product formulas
sigrank://formulas
Optional 24-stage RS05 SignalAF reference extension; not required for base SigRank compatibility
sigrank://classes
Current field-wide benchmark statistics (median, top 10%, top 1%) from the live leaderboard
sigrank://benchmarks
Prompts · 5
Compute your cascade metrics, compare against the live field, and get a one-line interpretation of where you stand.
Counterfactual analysis — finds the smallest pillar change needed to reach a target percentile.
Computes your operating archetype, dominant trait, and finds comparable operators on the live board.
Identifies efficiency leaks in your token cascade with severity, findings, and estimated yield impact per fix.
Scans the live leaderboard for unusual patterns — no input required.
How to use
Claude Desktop or claude.ai: add a custom connector (Customize → Connectors; on Team and Enterprise plans an owner adds it under Organization settings → Connectors) with this server URL: https://signalaf.com/api/mcp
Cursor or Cline: add to your MCP config:
{
"mcpServers": {
"sigrank_\u2014_ai_operator_benchmarking": {
"url": "https://signalaf.com/api/mcp",
"transport": "streamable-http"
}
}
}