oil-cover: 为小红书 AI 工具实操内容生成稳定、干净、精致封面的 Claude / Codex Skill(脚本模式 + Agent 自主执行)

by oil-oil · Codex Skill · ★ 218

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install oil-cover

git clone https://github.com/oil-oil/oil-cover.git ~/.claude/skills/oil-cover
git clone https://github.com/oil-oil/oil-cover.git ~/.codex/skills/oil-cover

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 57/100

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. Full audit →

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.

Quick Facts

Stars218
Forks22
LanguagePython
CategoryCodex Skill
Quality Score57/100
Last Updated2026-09-06
Created2026-06-25
Platformsclaude-code, codex, python
Est. Tokens~14k

About oil-cover

oil-cover 为小红书「AI 工具实操」内容生成稳定、清楚、干净、精致的视频封面的 Claude / Codex Skill。 方向是 真实屏幕证据 + Apple-like 产品视觉 + 清晰标题 + 无人物干净构图,一次性整图生成,不靠本地贴字拼图。 作者:oil 欧呦(@oil-oil) 封面示例 特点 视频选帧:把整段视频压成小 clip 交给多模态模型看完全片、按内容挑出最适合做封面的一帧(带理由),比盲采等距帧准得多。 完整视觉规范: 覆盖构图、背景层、字体标题、点缀、自动质检和提示词骨架。 默认三画幅:并行出小红书 竖版、B 站首页主封面 横版和个人空间伴随版 横版。 产品 Logo 自动匹配:内置 Claude / Codex / Cursor / Gemini / GitHub 等常用 AI 产品 Logo。 两种执行模式 模式偏好记在...

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How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools