by jnMetaCode · Claude Skill · ★ 509
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/plugin marketplace add jnMetaCode/ai-shortfilm-prompts
/plugin install ai-shortfilm-prompts@ai-shortfilm-promptsTaken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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.
| Stars | 509 |
| Forks | 96 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 69/100 |
| Last Updated | 2026-11-02 |
| Created | 2026-05-18 |
| Platforms | claude-code, python |
| Est. Tokens | ~17k |
ai-shortfilm-prompts ) ═══ -- ▶ 15s demo — generated from a prompt this repo's Skill wrote (prompt) -- The complete methodology + prompt library + Claude Code Skill behind Zombie Scavenger by Mx-Shell — the AI short that Hollywood director PJ Ace called "one of the best short fi
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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: