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 rawsun007 · Codex Skill · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-notch safe to install? View the security audit →
ClaudeNotch Approve Claude Code without leaving your work. ClaudeNotch puts every Claude Code permission prompt, question, and notification right in your Mac's notch. Read the diff, allow or deny with one key, and stay in your editor, no more tabbing back to the terminal every few seconds. What is ClaudeNotch? When
| Stars | 52 |
| Forks | 3 |
| Language | Swift |
| Category | Codex Skill |
| Quality Score | 64.2900545170846/100 |
| Last Updated | 2026-10-13 |
| Created | 2026-05-17 |
| Platforms | claude-code, codex |
| Est. Tokens | ~20k |
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claude-notch is Approve Claude Code from your Mac's notch. A native SwiftUI menu-bar app that surfaces Claude Code permission prompts, questions, cost and context usage, no tabbing back to the terminal.. It is categorized as a Codex Skill with 52 GitHub stars.
claude-notch is primarily written in Swift. It covers topics such as ai, ai-tools, anthropic.
You can find installation instructions and usage details in the claude-notch GitHub repository at github.com/rawsun007/claude-notch. The project has 52 stars and 3 forks, indicating an active community.
The top alternatives to claude-notch on Agent Skills Hub include CodeIsland, navigator, claude-historian-mcp. 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: