jevkit: Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay

by ariel-frischer · LLM Plugin · ★ 5

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 73/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiapiclassificationclideveloper-toolsjevjevkitjsonlinterlinting

Quick Facts

Stars5
Forks1
LanguageRust
CategoryLLM Plugin
LicenseMIT
Quality Score73/100
Open Issues7
Last Updated2026-10-16
Created2026-09-18
Platformscli, rust
Est. Tokens~25k

About jevkit

Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay

jevkit alternative? Top 6 similar tools

Looking for a jevkit alternative? If you're comparing jevkit with other llm plugin tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • open-alternative-jev by ikermoel · ⭐ 70

    Open-source alternative to TypeSafe's Jev: a System One style model layer that gives typed, calibrated decisio

  • jeview by andududu · ⭐ 65

    An unofficial local visualizer for Jev (TypeSafe): a live view of every call your code makes. Not affiliated w

  • HA-Jev by AboveColin · ⭐ 78

    Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as se

  • stuntd by bladedevoff · ⭐ 73

    Local proxy that learns your app's typed LLM decisions and answers them with a Laya head. Jev and OpenAI compa

  • fossil-mcp by yfedoseev · ⭐ 68

    The code quality toolkit for the agentic AI era. Find dead code, clones, and scaffolding across 15 languages.

  • awesome-jev by OmniJev · ⭐ 65

    🔥🔥 Papers, open reproductions and independent evaluations behind System One models and Jev.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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