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🎯 A Jev-powered decision engine and visual studio that prices uncertainty and asks the question that matters.
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- Updated Sep 2026
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Hinge-Jev
A TypeScript decision engine and visual studio that wraps TypeSafe Jev: developer-authored loss matrices price mistakes, exact Total Variation distance stress-tests probabilities, and clarifying questions are ranked by Value of Information minus interruption cost.
- Stars
- 3
- Language
- TypeScript
- License
- MIT
- Reading time
- 2 min
- Published by
- Community
- Author
- satiricalguru
- Last verified
- Oct 2026
- Languages
- TypeScript
- Capabilities
- Open sourceRequires API key
Highlights
- Prices mistakes with developer-authored loss matrices, then asks for one clarifying question only when its Value of Information exceeds the interruption cost.
- Stress-tests Jev probability distributions using exact Total Variation distance to catch miscalibration before acting.
- Conditions distributions dynamically as human answers eliminate worlds, and exports SHA-256 signed receipts for replayable governance.
- The local Decision Studio runs with example fixtures and zero configuration; live Jev inference needs TypeSafe early-access credentials in .env.
- Requires Node.js 22+; the README badge reports 13 of 13 tests passing.
Quickstart
bash
git clone https://github.com/satiricalguru/Hinge-Jev.git
cd Hinge-Jev
npm install
npm run devWatch out
Grounded in the truncated repository README and GitHub metadata reviewed on 2026-10-15; the README was cut off part-way through the .env setup, so the exact environment variable name is not reproduced here. All claims, including the 13/13 test badge, come from the project's own documentation.
Questions about this entry
Short answers drawn from the linked project or page.
A decision engine and local visual studio that pairs TypeSafe Jev's typed probability distributions with formal decision theory, so the operational tradeoff behind an automation decision, such as archiving versus deleting, becomes inspectable.
Hinge sends a Jev joint Choice question for the ambiguous request, then prices the resulting distribution with a loss matrix and a Total Variation stress test before deciding whether to ask a clarifying question or propose a bounded action.
Every candidate clarification is scored as its Value of Information minus the interruption cost it imposes. The studio asks at most a one-step clarification, and only when the net question value is above zero and risk remains within budget.
Clone the repo, run npm install and npm run dev, then open 127.0.0.1:5173. Example mode authors distributions as fixtures, and all loss evaluations, worst-case stress tests, Bayesian conditioning and SHA-256 receipts are computed in real time.
Hinge exports cryptographically signed receipts with SHA-256 digests, so a decision, its probabilities, the conditioning history and the chosen action can be replayed and audited later, which the README frames as governance rather than logging.
Node.js 22+ and npm. Live Jev inference additionally needs TypeSafe early-access credentials, which the README says go in a .env file using a key from console.typesafe.ai/keys.
satiricalguru's project under MIT. It is a single-step clarification loop rather than a general workflow engine, and the README's evidence is the author's own example fixtures plus the 13/13 test suite, not independent benchmarks.
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