samuraigpt/generative-media-skills

Multi-modal Generative Media Skills for AI Agents (Claude Code, Cursor, Gemini CLI). High-quality image, video, and audio generation powered by muapi.ai.

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Summary Information

Updated 41 minutes ago
Added to GitGenius on September 16th, 2026
Created on May 25th, 2023
Open Issues & Pull Requests: 4 (+0)
GitHub issues: Enabled
Number of forks: 493
Total Stargazers: 4,309 (+0)
Total Subscribers: 40 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 34.0 hours
Mean response time: 261.6 days
90th percentile: 937.8 days
Tracked items: 42

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Issue Activity (beta)

Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 96 days
Stale 30+ days: 2
Stale 90+ days: 1

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Generative Media Skills is a collection of agent tools that enable AI assistants like Claude Code, Cursor, and Gemini CLI to generate images, videos, and audio through a unified interface powered by muapi.ai.

The tool solves the problem of integrating high-quality generative media capabilities into AI agent workflows. Rather than requiring agents to call multiple disparate APIs, it provides a standardized set of skills that abstract away the complexity of different media generation services. The approach bundles image generation, video generation, and audio synthesis into composable tools that agents can invoke as part of their reasoning and execution loops.

Developers building AI agents that need to produce visual or audio content should consider this tool if they want to avoid managing multiple API integrations and authentication schemes. It suits projects where an AI assistant needs to generate media on demand as part of a larger workflow, such as content creation pipelines or interactive applications. The tool is positioned as an alternative to point solutions like Midjourney or Suno by offering a consolidated skill set across multiple modalities.

The project shows active development with regular commits addressing bug fixes and feature additions. Work spans implementation of new generation capabilities and refinement of the agent integration layer. The codebase receives ongoing maintenance with attention to both expanding supported media types and improving the reliability of existing integrations.