Original Summary

i ran jev-lint on my 99-page wiki: 1,267 questions, about 114 seconds, 16 findings (2 contradiction signals, 1 stale signal, 1 missing page, 12 unresolved markers). the estimated input-token cost based on returned usage was about $0.024. one real run, no accuracy benchmark. it's a python cli for obsidian vaults and markdown knowledge bases. typesafe jev, a typed judge model, scores possible contradictions and stale claims. TODO/FIXME/[?] markers and missing wikilink targets are checked locally. it writes a self-contained report.html and never edits notes. semantic flags are possible contradictions. read them as flags, never verdicts. the scan is candidate-based and does not compare every pair of claims. selected claim text goes to the jev api, so it is not fully offline. a jev api key is required and api usage is paid. the cli is mit-licensed with no locked paid version. https://jevlint.vayun.net https://github.com/vayungodara/jev-lint jev-lint is my project. agents wrote most of the code; i set the constraints and own the decisions.   submitted by   /u/Fit-Reaction242 [link]   [comments]

  • 情报分类：技术学习与提效
  • 分类依据：内容涉及技术、AI、软件工具或工程实践
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/18 19:28:45