
pythongiant/laya-drift on GitHub
- Stars
- 14
- Forks
- 0
- Language
- TypeScript
- Last push
- 23 Sep 2026
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An OpenCode plugin that embeds the running session state with Laya and scores how far it has drifted from the calibrated plan using weighted Jensen-Shannon divergence, shown live as a sidebar score.

Read from GitHub and X on . Counts change daily.
Declares typed input/output Signatures for LLM modules and optimizes the underlying prompts and weights against a metric. Its Signature abstraction is the closest widely-used open equivalent of Jev's typed-question interface. Star count is GitHub's rounded display figure.
Reproducible calibration and selective-risk benchmarks for Jev decisions inside DSPy workflows. Runs offline for confidence gating, latency and cost modelling without live API calls.
Composable Python toolkit for the Jev decision API bundling question builders, confidence gates, an evaluator, calibration tooling, a CLI, an MCP server over stdio and an agent skill.

Analysis of RLCD as a training target where stated probabilities should match how often the model is right. Flags calibration breaking under distribution shift, correlated errors compounding across workflows, and the difficulty of appeals without explanations.
Applies the same repeated-sampling self-consistency check to Choice questions so disagreement between samples becomes a signal to escalate.
Samples a noul question repeatedly and routes uncertain probabilities to human review while keeping the underlying values visible. Worked example uses insurance claim evaluation.