Generative-Media-Skills
Enables AI agents to generate production-grade images, video, and audio without maintaining separate integrations, reducing toolchain complexity and accelera…
Multi-modal Generative Media Skills for AI Agents (Claude Code, Cursor, Gemini CLI). High-quality image, video, and audio generation powered by muapi.ai.
- Generate product demo videos automatically from code documentation and architecture diagrams.
- Create training audio narration and accompanying visuals for onboarding new engineering team members.
- Produce marketing images and video clips from technical specifications for client presentations.
Enables AI agents to generate production-grade images, video, and audio without maintaining separate integrations, reducing toolchain complexity and accelerating multi-modal content workflows.
Engineering teams building AI agents that need integrated image, video, and audio generation capabilities within existing Claude or Cursor environments.
https://github.com/SamurAIGPT/Generative-Media-Skills
By SamurAIGPT
How to Get It
claude plugins install SamurAIGPT/Generative-Media-Skills
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 product demo videos automatically from code documentation and architecture diagrams
Trust Signals Auto-scanned
Community Pulse Emerging
Discussed on Hacker News
- Show HN: Generative Media Skills — Hacker News · 1 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 3,508 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): 3,508 GitHub stars; contributors unknown; last commit 0d ago; license MIT.