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Jevify (investigation prompt)

A single paste-in prompt for a coding agent that investigates what Jev, TypeSafe's structured decision model, could make possible in an existing project, from replacing parse-the-text calls to using semantic judgments as routine operations.
Stars
197
Reading time
2 min
Published by
Community
Author
ryana
Last verified
Oct 2026

ryana/jevify

User repository on GitHub

View on GitHub

Prompts to jev-ify your projects

Forks
6
Last pushed
Updated Sep 2026

Repo stats from the GitHub API, cached Oct 2026.

Highlights

  • The repo contains one prompt for investigating what Jev could make possible in an existing project.
  • Points the agent to TypeSafe's introduction, primitives, API reference, and llms.txt index.
  • Tells the agent to separate vendor claims, independently measured results, and its own hypotheses.
  • Frames the goal as making language understanding a routine computational operation across an app.
  • 197 stars, 6 forks, created and last pushed 2026-09-19; no language or licence is listed.

Watch out

README reviewed 2026-10-17; the repo is a prompt template only, with no licence, language metadata, code, benchmarks, or activity visible after its first day, so results depend entirely on the agent you paste it into.

Questions about this entry

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Other listings of this project

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44GitHub stars
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55GitHub stars
Toolkit that makes a model behind an OpenAI-compatible endpoint or running in-process answer typed choice, score, and yes/no questions from next-token probabilities in Jev API shape.
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4GitHub stars
Claude Code and Codex skill that audits a codebase for LLM call sites, proposes which routing, classification, and rubric-scoring decisions to convert to Jev, and reports latency and cost comparisons after the scope is approved.
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5GitHub stars
Inference engine around Qwen2.5-1.5B-Instruct for classification, yes/no judgements, and rubric scoring with 100% schema-valid JSON, no fine-tuning required.
Jev Tools & CLIs#community#awesomejev#catalog-import

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