eterna-image2image-skill: Experimental bilingual Codex skill for ETERNA-inspired image2image cinematic color and composition

by Cuimao777 · Codex Skill · ★ 175

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

Security audit verdict: SAFE · quality 54/100

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.

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.

ai-image-generationcinematiccodex-skillcolor-gradingeternaimage2image

Quick Facts

Stars175
Forks26
CategoryCodex Skill
LicenseMIT
Quality Score54/100
Last Updated2026-06-26
Created2026-06-26
Platformscodex
Est. Tokens~15k

About eterna-image2image-skill

ETERNA Image2Image Skill Experimental bilingual Codex skill for ETERNA-inspired image-to-image cinematic color, tone, composition, and anti-AI polish. This is an experimental skill that I am actively improving.

Compatible Skills

These tools work well together with eterna-image2image-skill for enhanced workflows:

  • codex-image — semantic(0.28)+complementary+similar_pop+shared_platform (50%)
  • Z-Image-Turbo-Windows — semantic(0.22)+complementary+rare_topics+similar_pop (47%)
  • codex-gpt-image — semantic(0.20)+complementary+similar_pop+shared_platform (47%)

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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:

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