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 trapoom555 · Claude Skill · ★ 94
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-paperloom safe to install? View the security audit →
Featured in: Personal Knowledge Skills
A Claude Code Plugin for Self-maintaining research knowledge graph for Claude Code + Obsidian. Knowledge graph view — 🟡 papers · 🟢 findings · 🟣 fields · 🔴 authors. Example shown: Typhoon.AI research papers. Per-paper info page — 4-section summary (incl. critique), atomic findings, metadata + quality scores,
| Stars | 94 |
| Forks | 11 |
| Language | JavaScript |
| Category | Claude Skill |
| License | Apache-2.0 |
| Quality Score | 68.6331381395118/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-28 |
| Created | 2026-04-23 |
| Platforms | claude-code, node |
| Est. Tokens | ~1297k |
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claude-paperloom is Claude Code Plugin for Self-maintaining research knowledge graph for Claude Code + Obsidian. It is categorized as a Claude Skill with 94 GitHub stars.
claude-paperloom is primarily written in JavaScript. It covers topics such as claude-code, claude-code-plugin, knowledge-graph.
You can find installation instructions and usage details in the claude-paperloom GitHub repository at github.com/trapoom555/claude-paperloom. The project has 94 stars and 11 forks, indicating an active community.
claude-paperloom is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to claude-paperloom on Agent Skills Hub include agent-second-brain, grainulator, obsidian-mcp-plugin. 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: