by tamaratran · AI Tool · ★ 167
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/tamaratran/jev-pruner.gitTaken 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 | 167 |
| Forks | 13 |
| Language | TypeScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 63/100 |
| Open Issues | 17 |
| Last Updated | 2026-09-30 |
| Created | 2026-09-18 |
| Platforms | claude-code, node |
| Est. Tokens | ~21k |
jev-pruner A Claude Code plugin that uses TypeSafe's Jev to trim noisy Bash output after the command runs, but before its result is sent back to the main LLM. This reduces the output carried into later turns without generating a summary. Using Codex? See Codex installation and usage. A hook wraps the Bash tool's result.
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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: