Ai Video Generation Skills
by @tate-kt
AI video, image generation. 40+ models — Sora, Veo 3, Kling, Seedance, GPT Image, Hailuo, WAN. Text-to-video, image-to-video, text-to-image,image-to-image.
clawhub install pixwith-ai-video-generation📖 About This Skill
name: pixwith-ai description: AI video, image generation. 40+ models — Sora, Veo 3, Kling, Seedance, GPT Image, Hailuo, WAN. Text-to-video, image-to-video, text-to-image,image-to-image. homepage: https://pixwith.ai user-invocable: false metadata: {"openclaw":{"homepage":"https://pixwith.ai"}}
Pixwith Media Generation
Use This Skill When
Use this skill when the user wants to work with Pixwith through MCP to:
Preconditions
On first install or first use of this skill, explicitly guide the user through setup before attempting any Pixwith tool call.
Use wording like:
"Before this skill can generate media, OpenClaw must be connected to Pixwith through MCP and you need a Pixwith API key.
If the user asks for a copyable MCP configuration, provide a ready-to-paste example using the Pixwith MCP endpoint and remind the user to replace the API key placeholder with their real key:
{
"mcpServers": {
"pixwith": {
"url": "https://api.pixwith.ai/mcp",
"headers": {
"Api-Key": "YOUR_PIXWITH_API_KEY"
}
}
}
}
If OpenClaw expects a different MCP configuration shape, adapt the same values to the host format instead of changing the endpoint or auth header.
Do not assume the user understands what MCP is. Describe it as the connection required for OpenClaw to use Pixwith.
If MCP tools are unavailable, tell the user Pixwith is not connected yet and repeat the setup guidance in plain language.
This skill assumes the Pixwith MCP server is already connected in OpenClaw and the following tools are available:
list_modelsget_model_schemaupload_imagegenerateget_task_resultget_creditsIf these tools are unavailable, stop and tell the user the Pixwith MCP server must be configured before this skill can work.
Every request requires a valid Pixwith Api-Key. If authentication fails, send
the user to https://pixwith.ai/api.
Core Workflow
1. Discover models
Call list_models first unless the user already provided a known model_id.
This step is mandatory because model availability is dynamic. Do not rely on static model lists in this skill package when choosing what to run.
type="image" for image jobstype="video" for video jobsmodel_id, name, and summary2. Inspect the selected model
Always call get_model_schema(model_id) before generate.
Treat input_schema as the source of truth for:
image_urls are allowedTreat min_credits from list_models only as a quick lower-bound cost hint:
input_schema.creditsDo not hardcode model parameters when schema data is available.
3. Check credits for expensive jobs
Call get_credits before expensive or long-running jobs, especially video jobs
or higher-resolution image jobs.
If credits are insufficient, do not retry automatically. Tell the user to
recharge at https://pixwith.ai/pricing.
4. Upload reference images when needed
Call upload_image when the image is local, private, temporary, or otherwise
unreliable as a public URL.
Use the returned Pixwith-hosted image_url in generate.image_urls.
5. Create the task
Call generate with:
input.promptinput.model_idinput.image_urls only when allowed by schemainput.options that conform to input_schema.optionsBefore submission:
list_models6. Poll until terminal state
Call get_task_result until status becomes terminal.
1: processing2: completed3: failedRecommended polling:
1. wait about 75% of estimated_time
2. poll once
3. if still processing, wait until around estimated_time
4. poll again
5. if still processing, poll every 10 seconds
Only expect result_urls when status is 2.
Guardrails
generate as an immediate result.code before trusting data.model_id prefix. Pass image_urls onlymodel_id. For example, Flux MCP IDsimage_urls and route to Flux Kontext when
image_urls is present.