by Oqura-ai · Claude Skill · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/Oqura-ai/optim-jev.git
claude plugin install optim-jev@optim-jevTaken 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 | 52 |
| Forks | 6 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 71/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-26 |
| Created | 2026-10-08 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~14k |
optim-jev Spend fewer tokens in long Claude Code sessions—without changing how you work. Jev-powered context compaction, model routing, and skill selection in one Claude Code plugin. Get started · Documentation · Architecture · Contributing <img src="assets/optim-jev.png" alt="optim-jev architecture: context compaction, model routing, and skill selection" width
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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: