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Analyze a user's codebase to verify it can use Runway's public API (server-side requirement)
npx skill4agent add runwayml/skills check-compatibility| File | Indicates |
|---|---|
| Node.js project |
| Python project |
| Go project |
| Rust project |
| Java/Kotlin project |
| Ruby project |
| PHP project |
package.jsonexpressfastifykoahapinesthononextnuxtremix@sveltejs/kitastroflaskdjangofastapistarlettetornadoaiohttpsanicstreamlitgradiopackage.jsonreactvuesvelteangularvite.config.tswebpack.config.jsindex.html<script>package.json@runwayml/sdkimport RunwayMLrequire('@runwayml/sdk')requirements.txtpyproject.tomlrunwaymlfrom runwayml import RunwayMLimport runwaymlnode --versionpython3 --version.env.env.example.env.localdotenvpython-dotenv## Runway API Compatibility Report
**Project type:** [Node.js / Python / etc.]
**Server-side capable:** [Yes / No / Partial]
**Runtime version:** [version] — [Compatible / Needs upgrade]
**Runway SDK installed:** [Yes / No]
**Environment variable support:** [Yes / No / Needs setup]
### Verdict: [COMPATIBLE / NEEDS CHANGES / INCOMPATIBLE]
[If COMPATIBLE]
Your project is ready for Runway API integration. Proceed with API key setup.
[If NEEDS CHANGES]
Your project needs the following changes:
1. [List specific changes needed]
[If INCOMPATIBLE]
Your project is frontend-only and cannot safely call Runway's API. Options:
1. **Add a backend** — Add an Express/FastAPI server or use a framework with server routes (Next.js, SvelteKit, etc.)
2. **Use a serverless function** — Add API routes via Vercel Functions, AWS Lambda, Cloudflare Workers, etc.
3. **Create a separate backend** — Build a thin API proxy that your frontend calls+setup-api-key