back
loading skill details...
Image generation skill. Automatically selects the best dlazy CLI image model based on the prompt.
---
name: dlazy-image-generate
version: 1.1.1
description: Image generation skill. Automatically selects the best dlazy CLI image model based on the prompt.
metadata: {"clawdbot":{"emoji":"🤖","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 <subcommand>."}}
---
# dlazy-image-generate
[English](./SKILL.md) · [中文](./SKILL-cn.md)
Image generation skill. Automatically selects the best dlazy CLI image model based on the prompt.
## Trigger Keywords
- generate image
- draw picture
- text to image
## 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 (`~/.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](https://dlazy.com)
2. Go to [dlazy.com/dashboard/organization/api-key](https://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](https://github.com/dlazyai/cli)
- **Maintainer**: dlazyai
- **npm package**: `@dlazy/cli` (pinned to `1.0.9` in this skill's install spec)
- **Homepage**: [dlazy.com](https://dlazy.com)
You can install on demand without persisting a global binary by running:
```bash
npx @dlazy/cli@1.0.9 <command>
```
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 — 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](https://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.<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`) |
### Examples
```bash
# 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.url
# Fan-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 — `--field -` satisfies the requirement when an upstream value exists. If stdin is empty, the CLI fails with `code: "no_stdin"`.
## Usage
This skill handles all image generation requests by selecting the best `dlazy` image model.
### Available Image Models
- `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 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 banana2`: General text-to-image model (optional 1 reference image), emphasizes speed and cost-effectiveness. Suitable for quick visual drafts, social media posts, and multi-size generation.
- `dlazy banana-pro`: High-quality text-to-image model (optional 1 reference image), suitable for key visuals, product shots, and brand style generation with higher detail requirements.
- `dlazy grok-4.2`: Minimalist text-to-image model, requires only prompt. Suitable for quick creative validation or scenarios with average quality requirements.
- `dlazy recraft-v3`: Stylized text-to-image model, supports aspect ratio and style control (realism/illustration, etc.). Suitable for brand KV, posters, and consistent visual content.
- `dlazy recraft-v3-svg`: Text-to-vector model, outputs SVG/vector-style results. Suitable for logos, icons, line art, and scalable design assets.
- `dlazy recraft-v4`: 1MP raster image generation with refined design judgment. Suitable for everyday creative work and fast iteration.
- `dlazy recraft-v4-vector`: Text-to-vector model that outputs SVG results. Suitable for logos, icons, and scalable design assets.
- `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 with 4MP-tier quality. Suitable for production-grade SVG assets and detailed illustrations.
- `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 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 viduq2-t2i`: Vidu image generation model, supports text + reference image, aspect ratio, and resolution control. Suitable for character art, cover images, and high-res generation.
- `dlazy jimeng-t2i`: Jimeng high-res text-to-image model, supports multi-ratio ultra-clear output and reference image constraints, suitable for commercial visuals and refined generation.
- `dlazy imageseg`: Image matting tool: separates foreground from background and returns transparent background URL, suitable for product image processing, character cutout, and composition.
- `dlazy image-replicate`: Image replicate tool: analyzes the visuals, composition, colors, lighting, and style of the source image, builds a replicate prompt, and hands it off to Seedream 4.5 to generate a new image in the same style.
- `dlazy superres`: Image super-resolution tool: enhances image clarity and details, returning enhanced URL, suitable for low-res asset restoration and upscaling.
**CRITICAL INSTRUCTION FOR AGENT**:
1. Select the most appropriate image model.
2. Run `dlazy <model_name> -h` 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 <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](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](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.don't have the plugin yet? install it then click "run inline in claude" again.