by erickong · Codex Skill · ★ 380
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g penechoTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 380 |
| Forks | 48 |
| Language | JavaScript |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 66/100 |
| Open Issues | 4 |
| Last Updated | 2026-07-20 |
| Created | 2026-07-14 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~17k |
Think with AI beyond the chat box. PenEcho is a shared canvas where handwriting, equations, diagrams, and spatial context become part of the conversation. Think on the canvas Put a question, equation, diagram, or half-formed idea anywhere on the canvas and pause. PenEcho reads your marks and their spatial relationships, then answers beside them.
These tools work well together with penecho for enhanced workflows:
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: