Agent skill · creative production · jeremylongshore
runway-core-workflow-b
Prepare, submit, and preserve Runway image-to-video or video-to-video work with validated media provenance. Use when a generation begins from an asset. Trigger with: "Runway image to video", "Runway video transformation", "upload media to Runway".
Why this skill is useful
Provides specific code examples and workflows for using Runway's AI video generation capabilities that the AI wouldn't reliably generate on its own.
What it needs
Requires pip, runwayml installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Runway Input-Media Transformation Workflow Overview Input media is part of the generation contract and the security boundary. Choose public HTTPS, data URI, or an ephemeral upload deliberately; verify rights, content, size, format, crop, expiry, and model compatibility before spending credits. Prerequisites An approved source asset with provenance and usage rights Current input constraints and exact model variant schema Temporary-upload and final-output retention policies Instructions Step 1: Classify the transformation Choose image-to-video, video-to-video, upscale, or another documented endpoint from the desired input and output—not from a copied sample. Record the expected preservation and allowed creative change. Step 2: Validate the asset Check MIME type, extension, byte size, dimensions, duration, codec, orientation, and moderation policy. Review auto-crop consequences when the source aspect ratio differs from the requested output. Step 3: Choose transport Use a reachable HTTPS URL for already hosted media, a data URI only for small inputs, or an ephemeral upload for local files. Never embed large video as base64 merely because a sample does. Step 4: Create an ephemeral upload safely For local media, use the SDK helper or the documented two-step upload. A runway:// URI lasts 24 hours, supports reuse within that period, and must not be treated as permanent storage. Step 5: Submit and track Validate the chosen model's input fields, persist the request fingerprint and task ID, then use bounded polling. Do not retry a failed upload URL; start a new upload as documented. Step 6: Validate transformed output Copy successful output to owned storage and compare duration, dimensions, codec, visible crop, continuity, brand constraints, and safety. Preserve both source and output checksums in the receipt. Authentication The Runway API secret remains server-side for uploads, generation, and task reads. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/runway-core-workflow-b