book-video-factory: Portable Codex skill for auditable, rights-aware Chinese book-review short-video workflows

by jaxxchen003 · Codex Skill · ★ 112

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

Featured in: OpenAI Codex Skills · Claude Video Editing & Remotion Skills

How to install book-video-factory

npx skills add jaxxchen003/book-video-factory --skill book-video-factory -g -y

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 71/100

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.

book-reviewcodexskillvideo-automation

Quick Facts

Stars112
Forks19
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score71/100
Open Issues2
Last Updated2026-08-17
Created2026-07-13
Platformscodex, python
Est. Tokens~16k

About book-video-factory

Book Video Factory Skill 简体中文 · English An installable Codex skill for running a rights-aware, local-first workflow for Chinese book-review short videos. It offers two separate styles: the original Bilingual Editorial Book Video and the new VOX-style Book Video, while keeping evidence, generation provenance, human approvals, costs, and release decisions auditable.

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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