Dlazy Generate

Generates images, videos, or audio by automatically selecting the appropriate dlazy model based on input prompts and media.

功能说明: 本技能涵盖 多种输入格式、图/视频/音频、选模型生成图/视频/音频 等核心能力。

功能说明: 本技能涵盖 时使用 等核心能力。

综合生成 Dlazy Generate

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A comprehensive generation skill. Can generate images, videos, and audio by automatically selecting the appropriate dlazy CLI model.

Trigger Keywords

• generate
• create image, video, audio
• multimodal generation

Authentication

All requests require a dLazy API key. The recommended way to authenticate is:

bash

This runs a device-code flow (also works in remote shells) and **automatically saves your API key** to the local CLI config — no manual copy/paste required.

### Alternative: Set the Key Manually

If you already have an API key, you can save it directly:

```bash
dlazy auth set YOUR_API_KEY

The CLI saves the key in your user config directory ($HOME/.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
2. Go to
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:
• Maintainer: dlazyai
• npm package: @dlazy/cli (pinned to 1.0.9 in this skill's install spec)
• Homepage:

You can install on demand without persisting a global binary by running:

bash

npx @dlazy/cli@1.2.0 <command>

Or, if you prefer a global install, the skill's metadata.SkillHub.install field declares the exact pinned version (npm install -g @dlazy/cli@1.2.0). 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 — 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 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.<jsonpath>	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>	Jsonpath into the whole envelope (@stdin:result.outputs[0].url)

示例

bash

dlazy seedream-4.5 --prompt "a red fox in snow" \
  | dlazy kling-v3 --image - --prompt "fox starts running"

dlazy seedream-4.5 --prompt "lighthouse at dawn" \
  | dlazy keling-tts --text "Welcome to the coast." --image @0.url

dlazy seedream-4.5 --prompt "city skyline" --n 4 \
  | dlazy superres --images @*

Required flags can be entirely sourced from the pipe — --field - satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with code: "no_stdin".

Usage

This is a comprehensive skill that routes generation requests to the appropriate dlazy model 基于 the user's intent.

Available Models by Category

Image Generation:

• dlazy banana-pro: High-quality text-to-image model (optional 1 reference image). Good for detailed key visuals, product shots, and brand-style imagery.
• dlazy banana2: General text-to-image model (optional 1 reference image), prioritizing speed and cost. Good for quick drafts, social posts, and multi-ratio generation.
• dlazy gpt-image-2: GPT Image 2 model for text-to-image and image editing. Supports generating images from text as well as editing and synthesizing images with reference inputs.
• dlazy grok-4.2: Minimalist text-to-image model, prompt-only. Good for quick concept validation or undemanding instant generation.
• dlazy image-replicate: Image replicate tool: analyzes the source's composition, color, lighting, and style, then uses Seedream 4.5 to generate a new image in the same style.
• dlazy imageseg: Image matting tool: separates foreground and returns a transparent-background URL. Good for product images, cutouts, and compositing.
• dlazy jimeng-t2i: Jimeng high-res text-to-image model with multi-ratio ultra-HD output and reference-image constraints. Good for commercial visuals and refined output.
• dlazy kling-image-o1: Kling image model, supports '<image_1>' placeholder in prompt for reference image binding. Suitable for multi-image constraints and high-fidelity generation.
• dlazy mj-imagine: Midjourney style generation, supports aspect ratio, Bot type, and output position (grid/U1-U4). Suitable for artistic and strongly stylized creative generation.
• dlazy qwen-image-2-pro: Alibaba Bailian qwen-image-2.0-pro general image generation. Excels at complex text rendering, multi-line layout, photorealistic detail, and strong semantic adherence — great for mixed text/image designs.
• dlazy recraft-v4: 1MP raster image generation with refined design judgment. Suitable for everyday creative work and fast iteration.
• dlazy recraft-v4-pro: 4MP high-resolution raster image generation. Suitable for print-ready assets and large-scale use.
• dlazy recraft-v4-pro-vector: High-fidelity text-to-vector model, 4MP-tier quality. Good for production SVG assets and detailed illustrations.
• dlazy recraft-v4-vector: Text-to-vector model that outputs SVG results. Suitable for logos, icons, and scalable design assets.
• dlazy seedream-4.5: High-quality text-to-image/image-to-image model, suitable for posters, realism, and creative scenes. Supports prompt + multiple reference images, outputting single high-res images (2K/4K).
• dlazy seedream-5.0-lite: Lightweight high-speed image generation model, suitable for batch generation, sketches, and low-cost iteration. Supports prompt + reference images, outputting 2K/3K images.
• dlazy superres: Image super-resolution tool: enhances image clarity and details, returning enhanced URL, suitable for low-res asset restoration and upscaling.
• dlazy viduq2-t2i: Vidu image model with text + reference image, ratio, and resolution control. Good for character art, covers, and high-res output.

Video Generation:

• dlazy happyhorse-1.0: Happy Horse 1.0 video model — 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 heygen-lipsync-speed: HeyGen Lipsync Speed: Fast lip-sync model, ideal for scenarios requiring rapid generation.
• 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-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; constrains shot start/end frames. Good for transitions and clearly resolved action.
• dlazy jimeng-omnihuman-1.5: Jimeng digital human model: combines any-ratio character/subject image with audio to generate high-quality digital human videos.
• 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 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 pixverse-c1: PixVerse C1 video model (strong on action, VFX, and high-motion scenes) — 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 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 sync-lipsync-3: fal.ai sync-lipsync v3 — given an input video and audio, generate a new video where the speaker's lip movement matches the audio. Good for dubbing, localization, and re-syncing virtual presenters.
• 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 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 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 videoretalk: Tongyi VideoRetalk lip sync / lip-sync (mouth sync, dubbing) video model — takes a talking-person video plus a voice audio track and regenerates the video so the speaker's mouth/lips match the new audio. Use this for lip syncing a person video to new speech. Optionally provide a reference face image to pick the target person when the video contains multiple faces.
• dlazy videoseg: Video human segmentation tool: invokes Aliyun's async SegmentVideoBody and returns a same-length black/white mask video, suitable for downstream compositing or matting.
• 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 wan2.7: Tongyi Wanxiang 2.7 video model — 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.

Audio Generation:

• dlazy doubao-tts: ByteDance Doubao speech synthesis model. Supports multiple languages, voices, and highly natural streaming audio output, suitable for news broadcasts and audiobooks.
• dlazy elevenlabs-dialogue: ElevenLabs eleven_v3 multi-voice dialogue: assign a different voice per line (up to 10) and render the whole conversation in one shot. Supports audio tags like [giggling], [whispers] — great for character dialogue, podcasts, and short skits. Before picking a voice, you can search for the right one via elevenlabs-search.
• dlazy elevenlabs-music: ElevenLabs music_v1 model — generates 10–300s original music from a natural-language prompt. Good for BGM, ads, and short-video soundtracks.
• dlazy elevenlabs-search: Search the ElevenLabs voice library by keyword, source, and category. Returns a playable preview for each matched voice so you can pick the right one before running TTS.
• dlazy elevenlabs-sfx: ElevenLabs text-to-sound model — generates 1–22s short sound effects from a description. Suitable for foley, ambience, alerts, and game SFX.
• dlazy elevenlabs-tts: ElevenLabs eleven_v3 text-to-speech with 12 curated multilingual voices and stability/similarity/style controls. Great for dubbing, audiobooks, and character dialog.
• dlazy elevenlabs-voice-clone: ElevenLabs Instant Voice Cloning (IVC). Upload a clean voice sample to clone a custom voice usable with ElevenLabs TTS.
• dlazy -2.5-tts: -powered high-quality text-to-speech. Supports bilingual (EN/CN) and various emotional voices.
• dlazy keling-sfx: Sound effect generation model: supports text-to-SFX and matching SFX/BGM for reference videos. Suitable for foley, ambient sounds, and short video audio completion.
• dlazy keling-tts: Text-to-speech model (TTS), supports language, voice, speed, and output format settings. Suitable for dubbing, audiobooks, and voice broadcasts.
• dlazy kling-audio-clone: Custom voice (Kling), cloned voice used for dubbing or binding to subjects.
• dlazy qwen-audio-clone: Alibaba Bailian qwen3-tts voice cloning. Upload a clean voice sample to clone a custom voice usable in subsequent TTS calls.
• dlazy qwen-tts: Alibaba Bailian qwen3-tts text-to-speech. Choose from curated system voices (including dialects) or design a custom voice from a natural-language description.
• dlazy suno-music: Suno V5.5 music generation. Inspiration mode (auto lyrics) or custom mode (manual style/title/lyrics). Generates music with or without vocals, with fine-grained controls over style weight, weirdness and audio weight.
• dlazy vidu-audio-clone: Clone a real human voice and use it to read the specified text.

CRITICAL INSTRUCTION FOR AGENT:

1. Determine the media type (image, video, or audio) requested by the user.
2. Select the most appropriate model from the list above.
3. Run dlazy <model_name> -h to check the required parameters for that specific model.
4. Execute the command (e.g., dlazy seedream-4.5 --prompt "...").

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 <prompt>' not specified
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 <key> and resume the task.

Tips

Visit https://dlazy.com for more information.

环境要求

运行环境

• Agent平台: 支持SKILL.md的任意AI Agent( Code / Cursor / Codex / CLI等)
• 操作系统: Windows / macOS / Linux

依赖说明

依赖项	类型	是否必需	获取方式
LLM API	API	必需	由Agent内置LLM提供

API Key 配置

• 本Skill基于Markdown指令,无需额外API Key(除内容中明确标注的外部API)

可用性分类

• 分类: MD+execute(纯Markdown指令,部分功能需要exec命令行执行能力)
• 说明: 基于Markdown的AI Skill,通过自然语言指令驱动Agent执行任务

能力矩阵

• A comprehensive generation skill
• Can generate images, videos, and audio
  \ by automatically selecti

快速指引

1. 确认运行环境满足依赖说明中的要求
2. 在AI Agent对话中调用本技能,提供必要的输入参数
3. 检查输出结果,根据需要进行后续处理

详细的输入输出格式请参考下方章节说明。

使用场景

场景	输入	输出
基础使用	用户请求	处理结果

不适用于：需要人工判断的复杂决策场景

问题汇总

Q1: 如何开始使用Dlazy Generate？

A: 请先阅读使用流程章节，确认环境满足依赖说明中的要求。

Q2: 遇到错误怎么办？

A: 请参考错误处理章节，按照表格中的处理方式操作。

Q3: Dlazy Generate有什么限制？

A: 请参考已知限制章节了解具体限制。

限制条件

• 需要LLM支持，无LLM环境无法使用
• 复杂场景可能需要人工辅助判断
• 性能取决于底层模型能力