by ruiwang20010702 · Codex Skill · ★ 103
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/ruiwang20010702/foursday.git
npx --no-install foursday setupTaken 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 | 103 |
| Forks | 2 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 54/100 |
| Last Updated | 2026-09-03 |
| Created | 2026-07-31 |
| Platforms | codex, node |
| Est. Tokens | ~13k |
Foursday A personal-memory-driven work twin for real projects. Trusted message → personal context → real workspace → verified work → natural reply. 简体中文 · Pilot test · Architecture · Install · Security · Contributing What it does Foursday is an AI work twin for people who want an agent to work inside their real projects—not a chatbot that needs a new workflow for every question.
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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: