jeff: Jeff 1 — local open-weight typed decision / fact-checking model (Jev-compatible)

by Gestalt-Lab · AI Tool · ★ 7

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Security audit verdict: SAFE · quality 57/100

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.

Quick Facts

Stars7
Forks1
LanguagePython
CategoryAI Tool
LicenseApache-2.0
Quality Score57/100
Last Updated2026-09-19
Created2026-09-19
Platformspython
Est. Tokens~15k

About jeff

Jeff 1 — local open-weight typed decision / fact-checking model (Jev-compatible)

Compatible Skills

These tools work well together with jeff for enhanced workflows:

  • JevAny — semantic(0.23)+complementary+shared_fw(huggingface)+same_lang+similar_pop+shared_platform (66%)

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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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