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 st0012 · Codex Skill · ★ 151
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cctop safe to install? View the security audit →
cctop Latest release | MIT license Keep an eye on your AI coding sessions. See which session is waiting on you. Jump back to the right tab, pane, thread, or project with a keystroke. Download for Apple Silicon | Intel | Website One compact menubar view for sessions across tools. Full launch video (MP4) Why cctop See at a glance which coding sessions are working, idle, or waiting on you. Jump directly to the right editor window, terminal pane, desktop thread, or project. Keep recent projects close without leaving a menubar app open all day. Find leftover ended-session worktrees, check Git safety, and remove the ones you are done with. Store session state locally as plain JSON. No analytics, telemetry, or session upload. Works Wit
| Stars | 151 |
| Forks | 21 |
| Language | Swift |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 67.6373769816979/100 |
| Open Issues | 18 |
| Last Updated | 2026-09-13 |
| Created | 2026-01-26 |
| Platforms | claude-code, codex |
| Est. Tokens | ~18k |
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cctop is A keyboard-first menubar app to monitor and jump between AI coding sessions — minimum setup required.. It is categorized as a Codex Skill with 151 GitHub stars.
cctop is primarily written in Swift. It covers topics such as agentic-workflow, ai-agents, ai-coding.
You can find installation instructions and usage details in the cctop GitHub repository at github.com/st0012/cctop. The project has 151 stars and 21 forks, indicating an active community.
cctop is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cctop on Agent Skills Hub include Awayke, MioIsland, CodeIsland. 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: