No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by iurykrieger · Claude Skill · ★ 91
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-bedrock safe to install? View the security audit →
Bedrock Turn any Obsidian vault into a structured Second Brain with AI agents Bedrock is a Claude Code plugin that automates Obsidian vault management through AI-powered skills. It organizes knowledge into 7 entity types following adapted Zettelkasten principles — entity detection, bidirectional linking, ingestion from external sources, deduplication, and sync. No build system. No runtime. Just markdown files, AI agents, and your Obsidian vault. Features 8 AI-powered skills — setup, ask, teach, preserve, compress, sync, healthcheck, and vaults 7 entity types — actors, people, teams, topics, discussions, projects, and fleeting notes External source ingestion — Confluence, Google Docs, GitH
| Stars | 91 |
| Forks | 8 |
| Language | HTML |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 75.1826297811773/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-05 |
| Created | 2026-04-13 |
| Platforms | claude-code |
| Est. Tokens | ~662k |
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claude-bedrock is Second Brain automation for Obsidian vaults — entity management, ingestion, compression, and sync via Claude Code skills. It is categorized as a Claude Skill with 91 GitHub stars.
claude-bedrock is primarily written in HTML. It covers topics such as ai, claude-code, claude-code-plugin.
You can find installation instructions and usage details in the claude-bedrock GitHub repository at github.com/iurykrieger/claude-bedrock. The project has 91 stars and 8 forks, indicating an active community.
claude-bedrock is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-bedrock on Agent Skills Hub include remember, agent-second-brain, skill-conductor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: