oil-visual — not yet audited

by oil-oil · Codex Skill · ★ 89

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

About oil-visual

制作统一漫画墨线风格的解释图与透明角色插图,用于概念、流程、比较和文章配图。

agent-skillscodeximage-generationvisual-explainer

Quick Facts

Stars89
Forks16
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score53.2249774950769/100
Last Updated2026-09-10
Created2026-07-20
Platformscodex, python
Est. Tokens~13k

Compatible Skills

These tools work well together with oil-visual for enhanced workflows:

oil-visual alternative? Top 6 similar tools

Looking for a oil-visual alternative? If you're comparing oil-visual with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • ask-user-questions-mcp by paulp-o · ⭐ 147

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  • agent-designer by appautomaton · ⭐ 130

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  • bria-skill by Bria-AI · ⭐ 66

    Claude Code skills for Bria AI - generate, edit, and transform images with Fibo, RMBG-2.0, and VGL structured

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Frequently Asked Questions

What is oil-visual?

oil-visual is 制作统一漫画墨线风格的解释图与透明角色插图,用于概念、流程、比较和文章配图。. It is categorized as a Codex Skill with 89 GitHub stars.

What programming language is oil-visual written in?

oil-visual is primarily written in Python. It covers topics such as agent-skills, codex, image-generation.

How do I install or use oil-visual?

You can find installation instructions and usage details in the oil-visual GitHub repository at github.com/oil-oil/oil-visual. The project has 89 stars and 16 forks, indicating an active community.

What license does oil-visual use?

oil-visual is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to oil-visual?

The top alternatives to oil-visual on Agent Skills Hub include mcp-image, ai-skills, skillport. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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:

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