xxg-portrait-rebuild-light — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by moskoo · Codex Skill · ★ 163

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

🔒 Is xxg-portrait-rebuild-light safe to install? View the security audit →

About xxg-portrait-rebuild-light

XXG Portrait Rebuild Light English 한국어 is an image-edit skill for existing portrait photos. It reconstructs the key light, fill, shadows, and background atmosphere with a director-led lighting workflow while restoring clean, healthy, low-contrast photographic skin microtexture. The skill changes the lighting without redrawing the person. It preserves identity, facial structure and proportions, natural slight asymmetry, expression, pose, camera view, and composition. It avoids plastic skin, grainy skin, dirty color variation, and fake depth made by exaggerating wrinkles. Key features Repairs plastic smoothness, excessive skin smoothing, and wax-like renderi

agent-skillsai-agentscodeximage-editingopenaiportrait-editingprompt-engineeringrelighting

Quick Facts

Stars163
Forks20
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score71.8672981599861/100
Last Updated2026-09-07
Created2026-08-11
Platformscodex, python
Est. Tokens~17k

Compatible Skills

These tools work well together with xxg-portrait-rebuild-light for enhanced workflows:

  • imagesorcery-mcp — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • gimp-mcp — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • MathRuler — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (59%)

xxg-portrait-rebuild-light alternative? Top 6 similar tools

Looking for a xxg-portrait-rebuild-light alternative? If you're comparing xxg-portrait-rebuild-light 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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Frequently Asked Questions

What is xxg-portrait-rebuild-light?

xxg-portrait-rebuild-light is `xxg-portrait-rebuild-light` is an image-edit skill for existing portrait photos. It reconstructs the key light, fill, shadows, and background atmosphere with a director-led lighting workflow while re. It is categorized as a Codex Skill with 163 GitHub stars.

What programming language is xxg-portrait-rebuild-light written in?

xxg-portrait-rebuild-light is primarily written in Python. It covers topics such as agent-skills, ai-agents, codex.

How do I install or use xxg-portrait-rebuild-light?

You can find installation instructions and usage details in the xxg-portrait-rebuild-light GitHub repository at github.com/moskoo/xxg-portrait-rebuild-light. The project has 163 stars and 20 forks, indicating an active community.

What license does xxg-portrait-rebuild-light use?

xxg-portrait-rebuild-light is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to xxg-portrait-rebuild-light?

The top alternatives to xxg-portrait-rebuild-light on Agent Skills Hub include ilab-gpt-conjure, agent-skills, gateway. 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:

View on GitHub → Browse Codex Skill tools