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 penecho · Codex Skill · ★ 2.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is penecho safe to install? View the security audit →
Think with AI beyond the chat box. PenEcho is a shared canvas where handwriting, equations, diagrams, and spatial context become part of the conversation. Quick Start • Recommended Models • Architecture • Discord A Kimi Open Source Friend <source media="(prefer
| Stars | 2,350 |
| Forks | 307 |
| Language | JavaScript |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 64.716414420676/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-13 |
| Created | 2026-07-14 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~20k |
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penecho is Think with AI beyond the chat box. A shared canvas for handwriting, equations, diagrams, and spatial reasoning.. It is categorized as a Codex Skill with 2.4k GitHub stars.
penecho is primarily written in JavaScript. It covers topics such as ai, canvas, claude.
You can find installation instructions and usage details in the penecho GitHub repository at github.com/penecho/penecho. The project has 2.4k stars and 307 forks, indicating an active community.
penecho is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to penecho on Agent Skills Hub include zcf, openpencil, dbhub. 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: