Dlazy Video Generate
by @dlazyai
Video generation skill. Automatically selects the best dlazy CLI video model based on the prompt.
clawhub install dlazy-video-generateπ About This Skill
name: dlazy-video-generate version: 1.1.1 description: Video generation skill. Automatically selects the best dlazy CLI video model based on the prompt. metadata: {"clawdbot":{"emoji":"π€","requires":{"bins":["npm","npx"]},"install":"npm install -g @dlazy/cli@1.0.9","installAlternative":"npx @dlazy/cli@1.0.9","homepage":"https://github.com/dlazyai/cli","source":"https://github.com/dlazyai/cli","author":"dlazyai","license":"see-repo","npm":"https://www.npmjs.com/package/@dlazy/cli","configLocation":"~/.dlazy/config.json","apiEndpoints":["api.dlazy.com","files.dlazy.com"]},"openclaw":{"systemPrompt":"When this skill is called, use dlazy
dlazy-video-generate
Video generation skill. Automatically selects the best dlazy CLI video model based on the prompt.
Trigger Keywords
Authentication
All requests require a dLazy API key. The recommended way to authenticate is:
This runs a device-code flow (also works in remote shells) and automatically saves your API key to the local CLI config β no manual copy/paste required.Alternative: Set the Key Manually
If you already have an API key, you can save it directly:
The CLI saves the key in your user config directory (~/.dlazy/config.json on macOS/Linux, %USERPROFILE%\.dlazy\config.json on Windows), with file permissions restricted to your OS user account. You can also supply the key per-invocation via the DLAZY_API_KEY environment variable.Getting Your API Key Manually
1. Sign in or create an account at dlazy.com
2. Go to dlazy.com/dashboard/organization/api-key
3. Copy the key shown in the API Key section
Each key is scoped to your dLazy organization and can be rotated or revoked at any time from the same dashboard.
About & Provenance
CLI source code: github.com/dlazyai/cli
Maintainer: dlazyai
npm package: @dlazy/cli (pinned to 1.0.9 in this skill's install spec)
Homepage: dlazy.com You can install on demand without persisting a global binary by running:
Or, if you prefer a global install, the skill's metadata.clawdbot.install field declares the exact pinned version (npm install -g @dlazy/cli@1.0.9). Review the GitHub source before installing.How It Works
This skill is a thin client over the dLazy hosted API. When you invoke it:
Prompts and parameters you provide are sent to the dLazy API endpoint (api.dlazy.com) for inference.
Any local file paths you pass to image / video / audio fields are uploaded to dLazy's media storage (files.dlazy.com) so the model can read them β the same flow as any cloud-based generation API.
Generated output URLs returned by the API are hosted on files.dlazy.com. This is the standard SaaS pattern; the skill itself does not access network or filesystem resources beyond what the dLazy CLI already handles. See dlazy.com for the full service terms.
Piping Between Commands
Every dlazy invocation prints a JSON envelope on stdout. Any flag value can be a pipe reference that pulls from the upstream command's envelope, so you can chain steps without copying URLs by hand.
| Reference | Resolves to |
| ------------------ | --------------------------------------------------------------- |
| - | Upstream's natural value for this field (scalar or array) |
| @N | The N-th output's primary value (e.g. @0 = first output url) |
| @N. | Drill into the N-th output (@0.url, @1.meta.fps) |
| @* | All outputs' primary values as an array |
| @stdin | The whole upstream JSON envelope |
| @stdin: | Jsonpath into the whole envelope (@stdin:result.outputs[0].url) |
Examples
Generate an image and feed its url straight into image-to-video
dlazy seedream-4.5 --prompt "a red fox in snow" \ | dlazy kling-v3 --image - --prompt "fox starts running"Generate an image, then add TTS narration over a still
dlazy seedream-4.5 --prompt "lighthouse at dawn" \ | dlazy keling-tts --text "Welcome to the coast." --image @0.urlFan-out: pass every upstream output url into a batch step
dlazy seedream-4.5 --prompt "city skyline" --n 4 \ | dlazy superres --images @* ``> Required flags can be entirely sourced from the pipe β
satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with code: "no_stdin".Usage
This skill handles all video generation requests by selecting the best
dlazy video model.Available Video Models
dlazy seedance-2.0: ByteDance's latest video generation model. Supports multi-modal reference (images, video, audio) to generate videos, as well as first/last frame and text-to-video modes.
dlazy seedance-2.0-fast: Fast version of ByteDance's Seedance 2.0. Generates videos faster with support for multi-modal references, first/last frame, and text-to-video.
dlazy veo-3.1: High-quality video generation model, supports text-to-video and single-image-driven video. Suitable for ad shorts and cinematic sequences (slower speed, higher quality).
dlazy happyhorse-1.0: Happy Horse 1.0 video model β one model covers text-to-video (t2v), first-frame-to-video (i2v), reference-to-video (r2v), and video editing (edit). The selected mode is automatically routed to the matching sub-model.
dlazy veo-3.1-fast: Fast video generation model, supports text-to-video and single/multi-image/first-last frame driven. Suitable for time-sensitive previews and rapid iterations.
dlazy kling-v3-omni: Kling Omni video model, supports multiple reference images, duration, mode (std/pro), and optional audio. Suitable for highly controlled video synthesis tasks.
dlazy kling-v3: Kling V3 general video model, supports text + up to 4 reference images, suitable for stable short video clips and daily creative workflows.
dlazy seedance-1.5-pro: ByteDance high-quality video generation model, supports text-to-video with optional first/last frame control for transitions, suitable for narrative shorts and continuous action scenes.
dlazy wan2.7: Tongyi Wanxiang 2.7 video model β one model covers text-to-video, first/last-frame-to-video, and reference-to-video: uses text-to-video when no images are provided, first/last-frame-to-video when frames are provided, and reference-to-video when reference images are supplied.
dlazy wan2.6-r2v: Tongyi Wanxiang video generation model (Standard), supports text + reference image, resolution, and shot type control, suitable for general short video production.
dlazy wan2.6-r2v-flash: Tongyi Wanxiang video generation model (Flash), optimized for speed and throughput, supports optional audio output, suitable for batch generation and quick trials.
dlazy pixverse-c1: PixVerse C1 video model (strong on action, VFX, and high-motion scenes) β one model covers text-to-video, image-to-video, first/last-frame-to-video, and reference-to-video: t2v when no images, i2v with first frame only, kf2v with first+last frames, r2v with reference images.
dlazy viduq2-i2v: Vidu image-to-video model, supports reference image-driven video, duration/resolution/ratio, and audio settings, suitable for image animation and short clips.
dlazy jimeng-i2v-first: Jimeng first-frame-to-video model, uses first frame + text to generate video. Suitable for single-shot scenes that naturally animate static images.
dlazy jimeng-i2v-first-tail: Jimeng first/last-frame video model, supports first and last frame constraints to control shot start/end states, suitable for transitions and clear action conclusions.
dlazy jimeng-dream-actor: Jimeng character/action-driven video model, supports reference image and video input, suitable for character acting, action transfer, and style-consistent generation.
dlazy jimeng-omnihuman-1.5: Jimeng digital human model, supports generating high-quality digital human videos from any aspect ratio image containing a character/subject combined with audio.
dlazy video-scenes: Scene split tool: uses ffmpeg to detect and split a video into scene clips, returning only the clip URLs without video content understanding.
dlazy video-replicate: Video replicate tool: extracts the first frame and audio from the source video, runs video understanding for a prompt, and returns a Seedance 2.0 replicate bundle (first frame + audio + video).
dlazy merge: Audio/video merging tool: merges multiple video and audio tracks based on clips and timeline config, suitable for final cuts, scoring, and post-production.
dlazy one-click-generation: Short-video generation pipeline. Configure subject, script, TTS voiceover, BGM, and subtitle styling.CRITICAL INSTRUCTION FOR AGENT:
1. Select the most appropriate video model.
2. Run
dlazy to check parameters.
3. Execute the command.Error Handling
| Code | Error Type | Example Message |
| ---- | ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------ |
| 401 | Unauthorized (No API Key) |
ok: false, code: "unauthorized", message: "API key is missing or invalid" |
| 501 | Missing required parameter | error: required option '--prompt |
| 502 | Local file read error | Error: Image file/Video file not found: C:\path\to\your\file |
| 503 | API request failed (no balance) | ok: false, code: "insufficient_balance" |
| 503 | API request failed (server error) | HTTP status code error (500 server crash) |
| 504 | Asynchronous task execution failed | === Generation Failed === / {Specific error reason returned by backend, for example "Prompt violates safety policy"} |> AGENT CRITICAL INSTRUCTION:
> 1. If the execution result returns
code: "insufficient_balance", you MUST explicitly inform the user that their credits are insufficient and guide them to recharge: https://dlazy.com/dashboard/organization/settings?tab=credits
> 2. If the execution result returns code: "unauthorized" or indicates missing API key, you MUST inform the user to get their API key from https://dlazy.com/dashboard/organization/api-key and save it using dlazy auth set Tips
Visit https://dlazy.com for more information.
π‘ Examples
# Generate an image and feed its url straight into image-to-video
dlazy seedream-4.5 --prompt "a red fox in snow" \
| dlazy kling-v3 --image - --prompt "fox starts running"Generate an image, then add TTS narration over a still
dlazy seedream-4.5 --prompt "lighthouse at dawn" \
| dlazy keling-tts --text "Welcome to the coast." --image @0.urlFan-out: pass every upstream output url into a batch step
dlazy seedream-4.5 --prompt "city skyline" --n 4 \
| dlazy superres --images @*
> Required flags can be entirely sourced from the pipe β --field - satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with code: "no_stdin".
π Tips & Best Practices
Visit https://dlazy.com for more information.