junaid1460

Masonry: generate images and video with models across providers

設計創意v1.1.6
作者:junaid1460更新於 2026-05-11共 5 個版本 · 最新版本釋出於 2026-03-05masonry-generate-image-and-video@clawhub_junaid1460/masonry-generate-image-and-video
圖片生成影片處理#Video Generation

據 AlphaMoat 統計,截至 2026-09,Masonry: generate images and video with models across providers 累計下載 2,724 次、獲 4 個星標,在全部 5,078 個 AI 技能中排名第 3,932 位,在「設計創意」分類(512 個)中排名第 382 位。

累計安裝
267
累計下載
2724
星標
4
全站排名
#3,932
全站前 78% · 「設計創意」前 75%
平台累計安裝累計下載星標評論
ClawHub ↗85259943
SkillHub ↗26727244—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

透過 masonry CLI 從文字提示生成 AI 圖片和影片,支援任務管理和模型瀏覽。需要 Masonry 訂閱(可在 https://masonry.so/pricing 開始免費試用);CLI 缺失時用 npm install -g @masonryai/cli 安裝或直接 npx @masonryai/cli。認證走 masonry login --remote(命令會列印授權 URL 交給使用者)或 masonry login --token <TOKEN>;已設定 MASONRY_TOKEN 與 MASONRY_WORKSPACE 的環境無需登入。圖片支援 --aspect(16:9、9:16、1:1)、--dimension、--model、--negative-prompt、--seed 等引數;影片支援 --duration(4、6、8 秒)、首幀/末幀圖片、--no-audio 等。命令立即返回 JSON,用 masonry job wait 等待後 masonry job download 下載,完成後輸出 MEDIA: 檔案路徑行。注意:絕不編造 job ID 或模型 key,只使用命令輸出中的值;無頭環境下不要執行不帶 --remote 或 --token 的 masonry login。

資料釋出於 2026-10-29

可以用來做什麼

  • 從文字提示生成圖片或影片(masonry image / masonry video)
  • 瀏覽可用模型及引數說明(masonry models list / models info)
  • 查詢、等待並下載生成任務結果(masonry job wait / job download)
  • 檢視本地歷史並同步未完成任務(masonry history list / history pending --sync)

什麼時候用

  • 想生成圖片、影片或其他視覺內容時
  • 想檢視可用的 AI 模型或檢查生成任務狀態並下載結果時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

用 Masonry 生成一張 16:9 的日落山景圖片
生成一段 4 秒的海浪拍打礁石影片
看看我的生成任務跑完沒有,完了幫我下載

月度資料趨勢

累計下載2724
1991238527782026-03 · 累計下載 20452026-05 · 累計下載 22502026-06 · 累計下載 23072026-07 · 累計下載 24412026-08 · 累計下載 25122026-09 · 累計下載 272426-0326-09
星標4
3452026-03 · 星標 42026-05 · 星標 42026-06 · 星標 42026-07 · 星標 42026-08 · 星標 42026-09 · 星標 426-0326-09

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份累計下載環比星標
2026-092724—4
2026-082512+2.9%4
2026-072441+5.8%4
2026-062307+2.5%4
2026-052250—4
2026-032045—4

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

4.2 KB · ClawHub v1.1.6
---
name: masonry
description: AI-powered image and video generation. Generate images, videos, manage jobs, and explore models via the masonry CLI.
metadata: {"openclaw":{"emoji":"🧱","requires":{"bins":["masonry"],"env":["MASONRY_TOKEN"]},"install":[{"type":"npm","package":"@masonryai/cli"}],"primaryEnv":"MASONRY_TOKEN","homepage":"https://masonry.so"}}
---

# Masonry CLI

Generate AI-powered images and videos from text prompts.
展開全部(共 147 行)
## When to use

- 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

## Prerequisites

A Masonry subscription is required. Start a free trial at: https://masonry.so/pricing

If the `masonry` command is not found, install it:
```bash
npm install -g @masonryai/cli
```

Or run directly: `npx @masonryai/cli`

## Authentication

If any command returns an auth error:

1. Run: `masonry login --remote`
2. The command prints an auth URL. Send it to the user.
3. User opens the URL in a browser, authenticates, and copies the token.
4. Run: `masonry login --token <TOKEN>`

For environments with `MASONRY_TOKEN` and `MASONRY_WORKSPACE` set, no login is needed.

## Workflow

### 1. Generate content

**Image:**
```bash
masonry image "a sunset over mountains, photorealistic" --aspect 16:9
```

**Video:**
```bash
masonry video "ocean waves crashing on rocks" --duration 4 --aspect 16:9
```

### 2. Handle the response

Commands return JSON immediately:
```json
{
  "success": true,
  "job_id": "abc-123",
  "status": "pending",
  "check_after_seconds": 10,
  "check_command": "masonry job status abc-123"
}
```

### 3. Wait and download

```bash
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
```

## Image flags

| Flag | Short | Description |
|------|-------|-------------|
| `--aspect` | `-a` | Aspect ratio: 16:9, 9:16, 1:1 |
| `--dimension` | `-d` | Exact size: 1920x1080 |
| `--model` | `-m` | Model key |
| `--output` | `-o` | Output file path |
| `--negative-prompt` | | What to avoid |
| `--seed` | | Reproducibility seed |

## Video flags

| Flag | Short | Description |
|------|-------|-------------|
| `--duration` | | Length in seconds: 4, 6, 8 |
| `--aspect` | `-a` | Aspect ratio: 16:9, 9:16 |
| `--model` | `-m` | Model key |
| `--image` | `-i` | First frame image (local file) |
| `--last-image` | | Last frame image (requires --image) |
| `--no-audio` | | Disable audio generation |
| `--seed` | | Reproducibility seed |

## Model discovery

```bash
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
```

## Job management

```bash
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
```

## Error codes

| Code | Meaning | Action |
|------|---------|--------|
| `AUTH_ERROR` | Not authenticated | Run auth flow above |
| `VALIDATION_ERROR` | Invalid parameter | Check flag values |
| `MODEL_NOT_FOUND` | Unknown model key | Run `masonry models list` |

## Guardrails

- 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.

## Feedback

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?

「設計創意」分類下的熱門技能

資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。