jev4pg: Established strong JEV based natural language to SQL performance and well-covered semantic operators

by Sheltercosmo · LLM Plugin · ★ 257

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

Security audit verdict: SAFE · quality 63/100

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.

databaseembeddingsjevjev-aillmnatural-language-querynl2sqlpgpostgrespostgresql

Quick Facts

Stars257
Forks30
LanguagePython
CategoryLLM Plugin
LicenseApache-2.0
Quality Score63/100
Last Updated2026-10-22
Created2026-09-23
Platformspython
Est. Tokens~17k

About jev4pg

jev4pg Natural language to SQL and semantic operators for PostgreSQL Website · Advantages · What you can build · Project guide · Installation · User guide · 简体中文 · Function reference · Documentation jev4pg turns the meaning in your data into reusable SQL capabilities. Define what “needs follow-up” means, query it like a column, and carry that definition into the next queue, report or application.

Compatible Skills

These tools work well together with jev4pg for enhanced workflows:

  • mnemiq — semantic(0.56)+complementary+rare_topics+same_lang+similar_pop+shared_platform (79%)
  • text2sql-framework — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (71%)

jev4pg alternative? Top 6 similar tools

Looking for a jev4pg alternative? If you're comparing jev4pg 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.

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  • text2sql-framework by Text2SqlAgent · ⭐ 154

    Agentic text-to-SQL SDK: hand the LLM one execute_sql tool and let it explore the schema, test queries, and se

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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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