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huncho

Dependency-free TypeScript SDK that turns Jev answers into named decisions with hysteresis thresholds, journaling and replay.

Library

This summary is based on how curated lists describe the project; its README was not available to review.

Overview

huncho is a TypeScript SDK described in the yibie/awesome-jev list. It wraps Jev's Noul, Choice and Score answers into named decisions that carry enter and exit thresholds, giving hysteresis so a decision does not flip back and forth around a single cut-off. Nested decision trees can be settled in one call.

It also keeps a JSONL journal of answers, lets you replay a threshold change over recorded answers without running inference again, and computes Brier scores and reliability for calibration. It can talk to TypeSafe directly, OpenRouter or the Vercel AI Gateway. No README could be fetched, so installation and API details are not confirmed here.

What the decision model decides

TypeQuestionAnswers
Yes / noNamed yes/no decision with enter/exit thresholds(inferred)yes · no
ChoiceNested decision tree branches settled in one call(inferred)—

How it works

  1. Define named decisions with enter and exit thresholds
  2. Ask Jev via TypeSafe, OpenRouter or Vercel AI Gateway
  3. Apply hysteresis to decide state changes
  4. Journal answers to JSONL
  5. Replay threshold changes and measure calibration offline

Strengths

  • Hysteresis prevents flapping decisions near a threshold
  • Replay tests threshold changes without new inference cost
  • Built-in Brier and reliability checks for calibration
  • No runtime dependencies

Caveats

  • README not available; details come from a list summary only
  • Maturity and tests unknown

At a glance

Type
Library
Language
TypeScript
Runtime
library
Has code
yes

Use cases and integrations

How curated lists describe it

  • TypeScript ecosystem: dependency-free SDK that turns Jev `Noul`, `Choice` and `Score` answers into named decisions with `enter`/`exit` thresholds (hysteresis), nested decision trees settled in one call, a JSONL journal, replay of a threshold change over recorded answers with no inference, and Brier/reliability calibration, over TypeSafe direct, OpenRouter or Vercel AI Gateway.

    yibie/awesome-jev

Frequently asked questions

What is hysteresis here?

Separate thresholds for entering and leaving a decision state, so small probability changes do not flip the outcome.

Can I test a new threshold without paying for inference?

Per the list summary, yes: it replays recorded answers from its journal.

Which providers does it support?

TypeSafe direct, OpenRouter and Vercel AI Gateway.

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