nirvana-os-engine: ready-to-run agentic operations

by gutomec · Codex Skill · ★ 79

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

Security audit verdict: SAFE · quality 62/100

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-frameworkagent-orchestrationagentic-aiai-agentsai-orchestrationantigravityautomationbunclaude-codecli

Quick Facts

Stars79
Forks24
LanguageTypeScript
CategoryCodex Skill
Quality Score62/100
Open Issues18
Last Updated2026-10-16
Created2026-06-16
Platformsclaude-code, cli, codex, gemini, node
Est. Tokens~17k

About nirvana-os-engine

Nirvana-OS Ready-to-run agentic operations. One sentence in. Finished work out. One command installs the engine and links it into every terminal agent it finds. Safe to run again any time. Prefer the skills route? installs the skill through skills.sh; on its first use it installs this same engine, and from then on you say "use nirvana". Documentation · Packs · [Illustrated install](https://gut

Compatible Skills

These tools work well together with nirvana-os-engine for enhanced workflows:

  • Multi-AI-Workflow — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)
  • dev-3.0 — semantic(0.31)+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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