NovaAudioAgent: open sourced personal agent + dual-brain voice assistant

by deepnovacore · Codex Skill · ★ 124

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

How to install NovaAudioAgent

npm install --global nova-audio-agent@0.2.3
npm install --global nova-audio-agent@preview

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

Security audit verdict: SAFE · quality 64/100

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.

agentagentic-aiaudioaudio-agentcodexpersonal-agentvibe-codingvibe-coding-assistant

Quick Facts

Stars124
Forks37
LanguageTypeScript
CategoryCodex Skill
LicenseApache-2.0
Quality Score64/100
Open Issues4
Last Updated2026-10-11
Created2026-08-16
Platformscodex, node
Est. Tokens~17k

About NovaAudioAgent

Nova Audio Agent English | 简体中文 An always-on voice agent with restrained proactivity and the capability of workspace management. News 2026-10-02 · v0.3.0 Preview — Nova grows from a voice assistant into a personal agent. Workbench main window: Todos, Ideas, Goals, Feeds, Tasks and Profile on the left, the conversation with Nova on the right; the orb stays as the collapsed form.

Compatible Skills

These tools work well together with NovaAudioAgent for enhanced workflows:

  • gini-agent — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
  • gini-agent — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
  • llm-wiki — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)

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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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