VaultAI: An AI chatbot plugin for Obsidian using the Gemini API for note summarization, content generation, and more

by 0xneobyte · Agent Tool · ★ 71

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

Security audit verdict: SAFE · quality 68/100

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.

aichatbotnotionnotion-aiobsidianobsidian-ai

Quick Facts

Stars71
Forks8
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score68/100
Open Issues5
Last Updated2026-04-11
Created2024-11-14
Platformsgemini, node
Est. Tokens~15k

About VaultAI

VaultAI - AI Writing Assistant for Obsidian Transform your note-taking with an intelligent AI writing assistant powered by Google's Gemini AI. VaultAI brings deep editor integration, custom prompts, and seamless content generation directly to your Obsidian workspace.

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Looking for a VaultAI alternative? If you're comparing VaultAI with other agent tool 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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    Free starter kit: Claude Code + Obsidian. Pre-configured vault with skills for projects, tasks, clients, and d

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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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