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Generative Media Skills

A library of more than 150 agent skills that teach AI coding assistants how to plan, generate, and check image, video, audio, and voice production work.

Generative Media Skills

Generative Media Skills is a collection of agent skills, organized into 25 categories, for producing and validating image, video, audio, voice, music, 3D, avatar, and other generative media inside AI coding assistants such as Claude Code, Codex, GitHub Copilot, and Cursor. Rather than only generating content, the skills combine researched production knowledge, comparisons of current providers, models, gateways, and costs, with executable guardrails and technical checks.

A typical workflow moves from choosing the right system for a task, through directing the work with cinematography, sound, and editing craft, to building the actual deliverable, running deterministic checks on the output, such as inspecting media, captions, 3D assets, or loudness, and finally handling provenance, rights, and delivery requirements. Each skill's own documentation file explains when and how to use any bundled executable resources. It can also connect to a separate project for orchestrated media workflows.

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  • Provenance gate

    github.com

    A deterministic authorization gateway that sits between an AI agent and its tools, tracing where each parameter of a side-effect call came from, and blocking the call or asking a human when the source does not check out.

  • A markdown framework of system rules that restates Isaac Asimov's Four Laws of Robotics as a set of prioritized loss calculations for large-language-model agents to follow, published as a discovery file for agents and crawlers to read.

  • Vitruvius

    github.com

    An engineering research agent that runs a discover, read, synthesize, verify and review loop over technical questions, reading sources directly rather than inferring from titles, and publishing its own scored verifier benchmark, weaknesses included.