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Split a judgment into Choice, Score and Noul, lint it, then measure it.
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MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code
agent-skillcalibrationclassificationclaude-codeconfidencejevllmmcpmcp-serverpythonsystem-onetypesafe-aitypescript
How builders describe it
MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code.
Design-time toolkit for using Jev from a coding agent, combining docs, a stdio MCP server, and an agent skill for decomposing judgments into Choice, Score, and Noul.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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