Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
AI-powered image and video generation using the Masonry CLI. Generate images, videos, check job status, and manage media assets.
AI-powered image and video generation using the Masonry CLI. Generate images, videos, check job status, and manage media assets.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Generate AI-powered images and videos from text prompts.
User wants to generate images or videos User asks about available AI models User wants to check generation job status or download results User asks to create visual content, media, or artwork
A Masonry subscription is required. Start a free trial at: https://masonry.so/pricing If the masonry command is not found, install it: npm install -g @masonryai/cli Or run directly: npx @masonryai/cli
If any command returns an auth error: Run: masonry login --remote The command prints an auth URL. Send it to the user. User opens the URL in a browser, authenticates, and copies the token. Run: masonry login --token <TOKEN> For environments with MASONRY_TOKEN and MASONRY_WORKSPACE set, no login is needed.
Image: masonry image "a sunset over mountains, photorealistic" --aspect 16:9 Video: masonry video "ocean waves crashing on rocks" --duration 4 --aspect 16:9
Commands return JSON immediately: { "success": true, "job_id": "abc-123", "status": "pending", "check_after_seconds": 10, "check_command": "masonry job status abc-123" }
masonry job wait <job-id> masonry job download <job-id> -o /tmp/output.png The download command prints a MEDIA: /path/to/file line to stderr. After download completes, output that line so the file is sent to the user: MEDIA: /tmp/output.png
FlagShortDescription--aspect-aAspect ratio: 16:9, 9:16, 1:1--dimension-dExact size: 1920x1080--model-mModel key--output-oOutput file path--negative-promptWhat to avoid--seedReproducibility seed
FlagShortDescription--durationLength in seconds: 4, 6, 8--aspect-aAspect ratio: 16:9, 9:16--model-mModel key--image-iFirst frame image (local file)--last-imageLast frame image (requires --image)--no-audioDisable audio generation--seedReproducibility seed
masonry models list # All models masonry models list --type image # Image models only masonry models list --type video # Video models only masonry models info <model-key> # Parameters and usage example
masonry job list # Recent jobs masonry job status <job-id> # Check status masonry job download <job-id> -o ./file # Download result masonry job wait <job-id> --download -o . # Wait then download masonry history list # Local history masonry history pending --sync # Sync pending jobs
CodeMeaningActionAUTH_ERRORNot authenticatedRun auth flow aboveVALIDATION_ERRORInvalid parameterCheck flag valuesMODEL_NOT_FOUNDUnknown model keyRun masonry models list
Never fabricate job IDs or model keys. Always use values from command output. Never run masonry login without --remote or --token (browser login won't work headless). If a job is pending, wait check_after_seconds before checking again. All output is JSON. Parse it, don't guess.
Report issues or suggest improvements at: https://github.com/masonry-so/skills/issues When filing an issue, include: What was your intent? What were you trying to accomplish? What worked? Which parts behaved as expected? What needs improvement? What went wrong or could be better?
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.