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fal.ai media generation -- unified access to AI models for images, videos, and audio through MCP server integration.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots.
Clean Architecture patterns for Android and Kotlin Multiplatform projects -- module structure, dependency rules, UseCases, Repositories, and data layer patterns.
Performance baseline and regression detection -- page performance, API latency, build times, and before/after comparison.
Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold.
Automated visual testing and interaction verification -- smoke tests, interaction tests, visual regression, and accessibility audits using browser automation.
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
| name | fal-ai-media |
| description | fal.ai media generation -- unified access to AI models for images, videos, and audio through MCP server integration. |
| origin | ECC |
Unified access to multiple AI models for creating images, videos, and audio content through an MCP server integration.
Configure MCP server in ~/.claude.json with a FAL_KEY environment variable obtained from fal.ai.
