pg-jev: Ask your Postgres tables questions in plain language. A PostgreSQL extension powered by TypeSafe's Jev

by realZachi · Agent Tool · ★ 1.3k

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

How to install pg-jev

git clone https://github.com/realZachi/pg-jev.git && cd pg-jev

Taken from the project's README on GitHub. Check the security audit before running it.

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.

Quick Facts

Stars1,256
Forks105
LanguageShell
CategoryAgent Tool
Quality Score73/100
Open Issues3
Last Updated2026-10-06
Created2026-09-17
Platformscli
Est. Tokens~12k

About pg-jev

jev — ask your Postgres tables questions in plain language Write the condition the way you would say it. Postgres does the rest. lets you filter, rank and classify rows with plain-language conditions. Every row is judged by TypeSafe's Jev, a System One model that returns calibrated probabilities instead of generated text. No index, no embeddings, no vector column.

Compatible Skills

These tools work well together with pg-jev for enhanced workflows:

  • jevmeter — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)
  • foreman — semantic(0.34)+complementary+same_lang+similar_pop+shared_platform (62%)
  • HA-Jev — semantic(0.32)+complementary+same_lang+similar_pop+shared_platform (61%)

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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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