football-prediction-avatar-video: Codex skill for verified Chinese football prediction avatar videos with official logos, captions, motion

by zlong6943-commits · Codex Skill · ★ 9

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

Featured in: Claude Video Editing & Remotion Skills

Security audit verdict: SAFE · quality 56/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 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.

Quick Facts

Stars9
Forks0
LanguagePython
CategoryCodex Skill
Quality Score56/100
Last Updated2026-09-05
Created2026-08-13
Platformscodex, python
Est. Tokens~14k

About football-prediction-avatar-video

Codex skill for verified Chinese football prediction avatar videos with official logos, captions, motion graphics, and approval gates.

Compatible Skills

These tools work well together with football-prediction-avatar-video for enhanced workflows:

  • fortune-liuyao-skill — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)
  • podcli — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)
  • prediction-market-agent-tooling — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)

More Codex Skill Tools

Explore other popular codex skill tools:

View all Codex Skill tools →

Popular Python Agent Tools

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 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