Xpersona
agentCLAWHUBUnverified

主图视频 Main Image Video

静态主图转主图视频。一张商品图 → 3–5 秒可上架的主图短视频。当用户说「主图视频」「图转视频」「让图动起来」「加个视频」时使用。 Skill: 主图视频 Main Image Video Owner: dlazyai Summary: 静态主图转主图视频。一张商品图 → 3–5 秒可上架的主图短视频。当用户说「主图视频」「图转视频」「让图动起来」「加个视频」时使用。 Tags: latest:1.0.15 Version history: v1.0.15 | 2026-10-10T01:53:36.146Z | user 例行版本更新 2026-10-10 v1.0.14 | 2026-10-08T01:45:33.674Z | user 例行版本更新 2026-10-08 v1.0.13 | 2026-10-04T01:45:30.558Z | user 例行版本更新 2026-10-04 v1.0.12 | 2026-10-02T05:17:48.984Z | user 例行版本更新 2026-10-02 v1.0.11 | 2026-09-30T01

OpenClaw
View on ClawHubHomepage

Rank

62

Safety

84

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.15

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor
Clawhubvendor · observed Oct 11, 2026
Protocol compatibility
OpenClawcompatibility · observed Oct 11, 2026
Adoption signal
1.1K downloadsadoption · observed Oct 11, 2026
Latest release
1.0.15release · observed Oct 10, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s170j1ymymrxasgd00dsk7tckx84cf45:main-image-video
  1. Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-dlazyai-main-image-video/snapshot"

Documentation

CLAWHUB

147,366 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: main-image-video
version: 1.0.15
description: 静态主图转主图视频。一张商品图 → 3–5 秒可上架的主图短视频。当用户说「主图视频」「图转视频」「让图动起来」「加个视频」时使用。
---

# main-image-video — 主图视频

主图坑位旁边那个视频位，大多数店铺是空的。它不需要重新拍，
**一张已有的主图就能生成**。

---

## 一、能力边界

| 能做 | 说明 |
| --- | --- |
| 图生视频 | 一张商品图 → 3–5 秒运动镜头 |
| 运镜控制 | 推、拉、环绕、俯仰、微距扫过 |
| 材质动态 | 面料飘动、金属反光扫过、液体晃动 |
| 批量 | 配合 [batch-image](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/batch-image/skill.md) 整批出 |

| 不能做 | 说明 |
| --- | --- |
| 长视频 | 超过 8 秒请用 [product-video-ad](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/product-video-ad/skill.md) 分镜串联 |
| 口播 | 用 [ugc-testimonial](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/ugc-testimonial/skill.md) |
| 改商品 | 视频模型会放大原图的瑕疵，先用 [item-repair](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/item-repair/skill.md) 修好 |

---

## 二、先配后端

视频模型 ID 因后端而异，**必须显式指定**，脚本不会替你猜：

```bash
export DLAZY_VIDEO_MODEL=<你账号里可用的视频模型 ID>
```

拼接与字幕需要 ffmpeg（本技能的单镜模式用不到，分镜才需要）。
完整说明见 [`references/video-backends.md`](references/video-backends.md)。

---

## 三、工具调用

```bash
node scripts/video.mjs --mode clip --task main-image-video \
  --image docs/flat-lay/example-output.jpg \
  --prompt 'Slow push-in on the model. The cable-knit sweater fibers catch the light softly. Subtle natural body sway. Camera stays level, no cuts.' \
  --seconds 3 \
  --save out/sku001-main.mp4

# 先看会发什么，不计费
node scripts/video.mjs --mode clip --task main-image-video --image x.jpg \
  --prompt '...' --dry-run
```

**参数约定**

| 参数 | 取值 | 理由 |
| --- | --- | --- |
| `--image` | 一张主图 | 竖版 3:4 或方图，分辨率越高越好 |
| `--seconds` | `3` ~ `5` | 主图位视频普遍偏短，超过 5 秒完播率掉得快 |
| `--brand` | `brand.yaml` | 让运镜与色调跟全店一致 |

---

## 四、Prompt 模板

**结构：运镜 + 主体动态 + 环境动态 + 约束**

```
<Camera move>. <What the product does>. <What the environment does>.
Keep the product identical to the reference image — same shape, color, texture, logo placement.
No cuts, no text overlay, no watermark. Photorealistic.
```

**运镜词表**

| 目标 | 英文 |
| --- | --- |
| 缓推 | `slow push-in` |
| 缓拉 | `slow pull-back reveal` |
| 环绕 | `smooth 30-degree orbit around the product` |
| 俯冲 | `gentle top-down tilt` |
| 微距扫过 | `macro pan across the surface texture` |

**材质动态词表**

| 品类 | 英文 |
| --- | --- |
| 针织 / 毛呢 | `fibers catch the light, fabric breathes subtly` |
| 真丝 / 雪纺 | `fabric ripples in a gentle draft` |
| 金属 / 珠宝 | `specular highlight sweeps across the metal` |
| 玻璃 / 液体 | `liquid settles, light refracts through the glass` |
| 皮革 | `soft sheen shifts across the grain` |

---

## 五、执行流程

1. **先检查静态图**。视频模型会放大原图的一切瑕疵。原图有崩就先修，别指望视频救。
2. **确认后端**。`DLAZY_VIDEO_MODEL` 没设就先问用户用哪个模型。
3. **单张试跑**。视频比图贵得多，先跑一条 3 秒的看运镜对不对。
4. **确认后再批量**。
5. **过一遍平台规格**。视频也有规格要求（时长、比例、体积），
   目前 [platform-compliance](https://github.com/dlazy-ai/ecommerce-skills/blob/main/skills/platform-compliance/skill.md) 只校验静态图，视频请人工对照平台文档。

---

## 六、常见问题

| 现象 | 原因 | 怎么办 |
| --- | --- | --- |
| 商品在动的过程中变形 | 运动幅度给太大 | 换成 `slow` / `subtle` 系的词，缩短时长 |
| 画面糊 | 原图分辨率不够 | 先用 [material-

_meta.json

{
  "ownerId": "kn7c5wgeajfcfvdfb5ceemvdb984cjpd",
  "slug": "main-image-video",
  "version": "1.0.15",
  "publishedAt": 1791597216146
}

references/provider-cli.md

<!-- 由 scripts/build-skills.mjs 从 shared/references/provider-cli.md 同步生成，不要直接改这里。 -->
# 后端调用参考

技能正文只写「要生成什么」。认证、计费、错误码、输出结构这些每个技能都一样的东西放在这里，
**用到时再读**，不占技能的常驻上下文。

---

## 一、认证

### 默认后端 dLazy

```bash
dlazy login            # 设备码流程，远程 shell 也能用，自动写入本地配置
dlazy auth set <KEY>   # 已有 key 时直接写入
```

key 存在用户配置目录（macOS/Linux `~/.dlazy/config.json`，Windows `%USERPROFILE%\.dlazy\config.json`），
权限限本机用户。也可以每次调用用环境变量 `DLAZY_API_KEY` 传入。

手动获取：登录 [dlazy.com](https://dlazy.com) → [API Key 页面](https://dlazy.com/dashboard/organization/api-key)。
key 按组织隔离，可随时轮换或吊销。

### 其他后端

本技能库不锁定单一厂商。配好任意一家的 key 即可跑：

| 后端 | 环境变量 | 说明 |
| --- | --- | --- |
| `dlazy` | `dlazy login` 或 `DLAZY_API_KEY` | 默认，最省事 |
| `openai` | `OPENAI_API_KEY` | 走 `/v1/images/edits` 与 `/v1/images/generations` |
| `gemini` | `GEMINI_API_KEY` | Nano Banana 系列 |
| `fal` | `FAL_KEY` | |
| `replicate` | `REPLICATE_API_TOKEN` | |
| `ark` | `ARK_API_KEY` + `ARK_MODEL` | 火山方舟，模型 ID 需按开通情况填 |

选路优先级：`--provider` 参数 > `PROVIDER` 环境变量 > 第一个配了 key 的 > `dlazy`。

```bash
node scripts/gen.mjs --doctor     # 看当前哪个后端可用
```

各后端的模型 ID 可用 `GEN_MODEL_OPENAI` / `GEN_MODEL_GEMINI` / `GEN_MODEL_FAL` /
`GEN_MODEL_REPLICATE` / `GEN_MODEL_ARK` 覆盖。**厂商目录会变，以各家最新文档为准。**

---

## 二、两种调用方式

### 方式 A：统一入口（推荐）

```bash
node scripts/gen.mjs --task <技能名> --prompt '...' --images a.jpg b.jpg --save out.jpg
```

它负责：后端选路、默认尺寸档位、失败重试（429/5xx 指数退避）、落盘建目录、成本估算。

```bash
node scripts/gen.mjs --task flat-lay --prompt '...' --dry-run   # 不调用不计费，只看要发什么
node scripts/gen.mjs --help
```

### 方式 B：直接用 dLazy CLI

不想引入 Node 依赖时，技能正文里的 `dlazy ...` 命令可以原样执行，效果等价。

```bash
npx @dlazy/[email protected] <command>     # 不装全局二进制
```

- CLI 源码：[github.com/dlazy-ai/cli](https://github.com/dlazy-ai/cli) · npm 包 `@dlazy/cli`

---

## 三、数据流向

调用 dLazy 时：提示词与参数发往 `api.dlazy.com`；传入的本地图片会上传到 `files.dlazy.com`
供模型读取；产出 URL 同样托管在 `files.dlazy.com`。这是云端生成 API 的通用形态。
换成其他后端时，数据流向对应厂商，不经过 dLazy。

---

## 四、输出结构

`gen.mjs`（加 `--json`）：

```json
{
  "ok": true,
  "task": "flat-lay",
  "provider": "dlazy",
  "model": "gpt-image-2",
  "files": ["docs/flat-lay/output-sku001.jpg"],
  "texts": [],
  "estimatedCredits": 60,
  "elapsedMs": 58213
}
```

dLazy CLI 原生：

```json
{
  "ok": true,
  "result": {
    "tool": "gpt-image-2",
    "data": { "urls": ["https://files.dlazy.com/data/ai/....jpg"] },
    "savedPath": "docs/flat-lay/example-output.jpg"
  }
}
```

加 `--no-wait` 的异步任务不返回 `data`，返回 `task: { generateId, status }`，
用 `dlazy status <generateId> --wait` 轮询。

文本类模型（如质检）产出在 `result.data.texts[0]`：

```bash
dlazy claude-sonnet-5 --prompt '...' --images x.jpg \
  | python3 -c 'import sys,json;print(json.load(sys.stdin)["result"]["data"]["texts"][0])'
```

---

## 五、错误处理

| Code | 类型 | 示例 |
| --- | --- | --- |
| 401 | 未授权 / 无 key | `ok: false, code: "unauthorized"` |
| 501 | 缺必填参数 | `error: required option '--prompt <prompt>' not specified` |
| 502 | 本地文件读不到 | `Error: Image file not found: ...` |
| 503 | 余额不足 | `ok: false, code: "insufficient_balance"` |
| 503 | 服务端错误 | `HTT

references/video-backends.md

<!-- 由 scripts/build-skills.mjs 从 shared/references/video-backends.md 同步生成，不要直接改这里。 -->
# 视频后端配置

图像模型的默认值写死在 `lib/tasks.json` 里，视频模型没有——**因为各家的视频模型
ID 差异大、更新快，写死只会误导**。所以视频技能要求你显式指定。

## 指定模型

```bash
export DLAZY_VIDEO_MODEL=<你账号里可用的视频模型 ID>
# 或每次调用时
node scripts/video.mjs --mode clip --task main-image-video --model <id> ...
```

没设会直接报错，不会拿一个猜的模型名去跑。

## 各后端

| 后端 | 怎么配 | 说明 |
| --- | --- | --- |
| `dlazy` | `DLAZY_VIDEO_MODEL` | 用 `dlazy --help` 看当前账号可用的视频工具 |
| `fal` | `FAL_KEY` + `GEN_MODEL_FAL=<视频模型路径>` | 产出在 `videos[]` 或 `video.url` |
| `replicate` | `REPLICATE_API_TOKEN` + `GEN_MODEL_REPLICATE=<owner/model>` | 产出为 URL |

图生视频时参考图走 `--images`，与图像技能一致。

## 合成依赖

拼接与字幕需要 ffmpeg：

```bash
brew install ffmpeg        # macOS
apt install ffmpeg         # Debian/Ubuntu
```

没装也能跑——片段照常生成，脚本会输出 `concat.txt`，装好后一条命令补拼。

## 字幕的三级降级

1. **烧录进画面**：需要 ffmpeg 带 libass。很多发行版的预编译包没有。
2. **软字幕轨**：`-c:s mov_text` 封进 MP4，播放器可开关。几乎总能成。
3. **都不行**：`.srt` 留在产物目录旁边，可导入剪辑软件。

脚本自动逐级尝试，不用你判断。查本机是否支持烧录：

```bash
ffmpeg -hide_banner -filters | grep ' subtitles '
```

## 分镜文件

```json
{
  "shots": [
    { "id": "s1", "seconds": 3, "image": "main.jpg",
      "prompt": "Slow push-in on the product, soft light sweeps across the surface.",
      "caption": "三层加厚，零下也不怕" }
  ]
}
```

`caption` 会按 `seconds` 累加时间轴自动生成 SRT，不用手对时间码。

scripts/lib/tasks.json

{
  "_note": "技能 → 默认模型与参数。dlazy 列为默认后端的模型名；其他后端走 providers.mjs 的通用映射，可用 GEN_MODEL_<PROVIDER> 覆盖。",
  "_credits": { "gpt-image-2": 60, "seedream-5.0": 30, "seedream-5.0-pro": 45, "banana-pro": 25, "claude-sonnet-5": 3 },
  "tasks": {
    "flat-lay":                { "model": "gpt-image-2",      "size": "1024x1536", "quality": "high",   "format": "jpeg" },
    "wear-everything":         { "model": "gpt-image-2",      "size": "1024x1536", "quality": "medium", "format": "jpeg" },
    "image-fusion":            { "model": "seedream-5.0",     "size": "3:4",       "resolution": "2k" },
    "one-shot":                { "model": "gpt-image-2",      "size": "1024x1536", "quality": "medium", "format": "jpeg" },
    "fission-pattern":         { "model": "gpt-image-2",      "size": "1024x1536", "quality": "medium", "format": "jpeg" },
    "item-detail":             { "model": "seedream-5.0-pro", "size": "3:4",       "resolution": "2k" },
    "creative-scene":          { "model": "banana-pro",       "size": "1024x1536", "format": "jpeg" },
    "batch-image":             { "model": "seedream-5.0",     "size": "3:4",       "resolution": "2k" },
    "to-3d":                   { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "clothing-extraction":     { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "fabric-on-body":          { "model": "gpt-image-2",      "size": "1024x1536", "quality": "high",   "format": "jpeg" },
    "clothing-detail":         { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "clothing-grass-planting": { "model": "gpt-image-2",      "size": "1024x1536", "quality": "medium", "format": "jpeg" },
    "item-selling-point":      { "model": "seedream-5.0-pro", "size": "1:1",       "resolution": "2k" },
    "item-change-background":  { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "remove-watermark":        { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "material-enhancement":    { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "item-repair":             { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "detect-task":             { "model": "claude-sonnet-5",  "text": true },
    "listing-optimizer":       { "model": "gpt-image-2",      "size": "1024x1024", "quality": "high",   "format": "jpeg" },
    "cross-border-localize":   { "model": "seedream-5.0-pro", "size": "1:1",       "resolution": "2k" },
    "brand-kit":               { "model": "gpt-image-2",      "size": "1024x1536", "quality": "high",   "format": "jpeg" },
    "platform-compliance":     { "model": "claude-sonnet-5",  "text": true },
    "main-image-video":        { "model": "$DLAZY_VIDEO_MODEL", "video": true },
    "product-

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Machine-readable data

The same record, as JSON, for agents and crawlers.

{
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      "label": "Vendor",
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      "href": "https://clawhub.ai/dlazyai/skills/main-image-video",
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      "observedAt": "2026-10-10T01:53:36.146Z",
      "isPublic": true
    }
  ]
}

Record generated Oct 11, 2026.

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