neug: The one data index for your agentic applications

by alibaba · Agent Tool · ★ 176

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

How to install neug

pip install neug
npm install @graphscope-neug/neug

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

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.

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.

agent-toolscode-graphcodegraphcontextgraph-analyticsgraph-database-vector-databasehybrid-searchknowledge-graphsllmwiki

Quick Facts

Stars176
Forks35
LanguageC++
CategoryAgent Tool
LicenseApache-2.0
Quality Score67/100
Open Issues50
Last Updated2026-11-06
Created2026-03-02
Est. Tokens~18k

About neug

The one data index for your agentic applications NeuG (pronounced "new-gee") is a high-performance, graph-native transactional database that runs embedded in your application or behind a service. It provides durable storage, explicit transactions, Cypher-native querying, and in-place graph analytics. Built on this data foundation, NeuG i

Compatible Skills

These tools work well together with neug for enhanced workflows:

  • samyama-graph — semantic(0.43)+complementary+similar_pop (50%)
  • rushdb — semantic(0.34)+complementary+similar_pop (47%)
  • NornicDB — semantic(0.34)+complementary+similar_pop (47%)

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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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