remotion-dev/skills

Agent Skills

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Summary Information

Updated 30 minutes ago
Added to GitGenius on September 15th, 2026
Created on January 19th, 2026
Open Issues & Pull Requests: 21 (+0)
GitHub issues: Enabled
Number of forks: 519
Total Stargazers: 4,581 (-1)
Total Subscribers: 17 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 17.2 hours
Mean response time: 3.7 days
90th percentile: 6.7 days
Tracked items: 2

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Open issues: 10
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 90 days
Stale 30+ days: 9
Stale 90+ days: 4

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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

Remotion Agent Skills is a collection of specialized prompts and knowledge modules designed to guide AI coding assistants in working with Remotion projects.

The tool addresses the challenge of helping AI agents understand Remotion-specific best practices and workflows. It provides a structured set of skills that cover distinct areas of Remotion development, from project creation and markup to rendering, maps, captions, and SaaS architecture. Each skill acts as a focused knowledge module that an AI agent can reference when responding to developer prompts, ensuring guidance aligns with Remotion conventions and capabilities.

Developers should adopt these skills if they use AI coding assistants like Claude Code, Cursor, or similar tools within Remotion projects. The skills are most valuable for teams building video generation applications who want their AI assistant to understand Remotion-specific patterns and best practices. Installation is straightforward, offered as an option when creating new Remotion projects or installable via command line. The skills cover a broad range of use cases: basic project setup, React component patterns, video rendering, map animations, caption handling, and building Remotion-powered SaaS products. A catch-all skill for general best practices exists for situations where a more specific skill is unclear.

The project maintains documentation that stays synchronized with the skills themselves through an automated generation process, indicating active upkeep of the knowledge modules. The skills are designed to be discoverable and actionable, with example prompts provided for each module to guide users on when and how to invoke them.