ai-shortfilm-prompts
Reduces production friction for teams building AI video content by providing battle-tested prompt templates and structured methodology validated through awar…
Methodology + prompts + Claude Code Skill behind Zombie Scavenger by Mx-Shell — the AI short PJ Ace called "one of the best short films I've seen in years." Works with Sora · Kling · Veo · Seedance.
- Generate detailed video prompts for AI film tools like Sora or Kling from story ideas
- Create structured scene descriptions and shot lists for short film production workflows
- Develop narrative frameworks and visual direction guidelines for AI video generation
Reduces production friction for teams building AI video content by providing battle-tested prompt templates and structured methodology validated through award-recognized output, accelerating time-to-quality for marketing and creative deliverables.
Creative technologists and product marketing teams generating AI video assets for campaigns or portfolio pieces.
https://github.com/jnMetaCode/ai-shortfilm-prompts
By jnMetaCode
How to Get It
claude plugins install jnMetaCode/ai-shortfilm-prompts
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate detailed video prompts for AI film tools like Sora or Kling from story ideas
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 206 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 206 GitHub stars; contributors unknown; last commit 0d ago; license MIT.