Runwayml
Analysis
This is a straightforward Runway API instruction skill; it requires a Runway API key, an SDK install, and sending prompts or media to Runway, all of which are disclosed and aligned with its purpose.
Findings (3)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Checks for instructions or behavior that redirect the agent, misuse tools, execute unexpected code, cascade across systems, exploit user trust, or continue outside the intended task.
Install the Node.js SDK: `npm install @runwayml/sdk`
The setup step pulls an external npm package without pinning a version; this is user-directed and purpose-aligned, but it is still a package provenance consideration.
Checks whether tool use, credentials, dependencies, identity, account access, or inter-agent boundaries are broader than the stated purpose.
compatibility: Requires internet access and a RunwayML API key stored as RUNWAYML_API_SECRET environment variable.
The skill needs a service credential to act on the user's Runway account; this is expected for the stated purpose, but users should notice that the registry metadata did not declare the credential requirement.
Checks for exposed credentials, poisoned memory or context, unclear communication boundaries, or sensitive data that could leave the user's control.
Generate AI videos, images, and audio using Runway's API... supporting ... third-party models from Google (Veo) and ElevenLabs.
The skill discloses that prompts and media are sent to Runway and may involve partner models; this is central to the media-generation purpose, but it creates an external data boundary users should understand.
