Token导航 LogoToken导航

Agent Skill · 开发

fashion-video-creator(时尚视频创作者)

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

fashion-video-creator 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 9,339。

总安装 2,756周安装 116GitHub Stars 公开资料未说明下载 965核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:fashion-video-creator(时尚视频创作者)
来源仓库:https://github.com/dingtom336-gif/fashion-video-creator
安装命令:
openclaw skills install fashion-video-creator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install fashion-video-creator

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

生成虚拟模特图与穿搭视频,支持单条或批量模式输出视觉素材。适合时尚博主、品牌方或内容创作者制作宣传视频与造型展示。需提供服装描述、模特姿态及视频时长要求,系统自动生成 Seedream 图像与 Seedance 视频 Prompt。涉及人物肖像使用时须确保版权合规,商用前应完成内容审核流程。

批量处理时注意 GPU 资源消耗,建议分批次提交任务以控制成本。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install fashion-video-creator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

fashion-video-creator 怎么安装?

在终端执行 openclaw skills install fashion-video-creator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

fashion-video-creator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

fashion-video-creator 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

fashion-video-creator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

fashion-video-creator 用的人多吗?

公开数据是累计安装 2,756 次,近一周安装 116 次,下载 965 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

fashion-video-creator 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
fashion-video-creator

时尚视频创作者 · 本页

2,756—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
fashion-video-creator
description
穿搭视频创作 — 生成虚拟模特图(Seedream 4.5/5.0) + Seedance 2.0 视频Prompt + 操作手册(SOP)。支持单条和批量模式。Use when: '帮我做穿搭视频', '生成模特图', 'generate outfit video', '批量生成穿搭prompt', '穿搭创作', '虚拟模特'. Do NOT use for video analysis/reverse engineering — use viral-video-replicator instead.
version
1.1.0
compatibility
Claude Code, Claude.ai, and all SKILL.md-compatible agents

Skill: fashion-video-creator

Overview

Generate complete assets for fashion e-commerce videos from scratch: a virtual model image (Seedream text-to-image) + a Seedance 2.0 video prompt with dialogue, actions, and scene + an operator SOP for the Jimeng platform. Supports single and batch modes.

When to Activate

User query contains any of:

  • "穿搭视频", "outfit video", "生成模特", "虚拟模特"
  • "seedance prompt", "穿搭创作", "带货视频", "带货短视频"
  • "帮我做个穿搭视频", "批量生成穿搭", "batch prompt"
  • "帮我拍个带货视频", "我有件衣服想做个展示视频", "做个穿搭短视频"
  • "generate fashion video", "create outfit content"

Do NOT activate for:

  • Analyzing / reverse-engineering existing videos -> use viral-video-replicator
  • "这个视频怎么拍的", "帮我复刻这个视频" -> use viral-video-replicator
  • Pure image generation without video prompt -> direct Seedream API call
  • Non-fashion video generation -> not applicable

Prerequisites

This skill requires a Volcano Engine (火山方舟) account with Seedream model access.

Required: ARK_API_KEY + Seedream model/endpoint ID
Optional: None (all other logic is local)

Clarification Flow

Phase 1: API Key Acquisition

Ask these questions IN ORDER. Use plain language — the user may not be technical.

Q1: Image Generation Service

"你需要先有一个能生成图片的 AI 服务账号。目前这个工具使用的是火山方舟平台的 Seedream 模型。 你有火山方舟的账号吗?如果有,请提供你的 API Key(在火山方舟控制台 -> API Key 管理中可以找到)。"

If user has no account -> STOP. Guide them to register at 火山方舟. Do NOT proceed without API key.

Q2: Model Version

"火山方舟上有两个版本的图片生成模型: - Seedream 5.0(推荐):理解能力更强,生成的人像更自然,每张约 0.22 元 - Seedream 4.5:可以更精细地控制细节,每张约 0.32 元 你开通了哪个?需要提供模型ID或接入点ID。"

Phase 2: Mandatory Recommendations

MUST show before proceeding. These are not optional tips — violating them degrades output quality:

============================================================
API Configuration — Mandatory Recommendations
============================================================

[REQUIRED] Seedream 5.0 endpoint preferred
  WHY: 5.0 uses internal Chain-of-Thought reasoning, making natural
  language prompts significantly more effective. 4.5 relies on keyword
  stacking which loses semantics in complex body descriptions.
  If only 4.5: use model ID doubao-seedream-4-5-251128 or newer.

[REQUIRED] Realism scale 40-60
  WHY: Below 30 the output looks cartoonish (Pixar-style), unsuitable
  for product videos that need believable human models. Above 80 triggers
  uncanny valley artifacts and skin texture glitches.

[WARNING] Using older models or non-recommended endpoints will produce
noticeably worse portrait realism and clothing detail accuracy.
============================================================

Phase 3: Mode Selection

"你要生成几条视频?单条还是批量?"

Phase 4: Creative Parameter Collection

Collection strategy — ask in 2 rounds, never more than 4 questions per round:

Round 1 (required — must have before executing):

  1. Model gender (female/male) — default: female
  2. Garment type (dress/top/pants/jacket/suit/casual) — NO default, must ask. WHY: "default" type produces generic dialogue without product-specific selling points. Defensive fallback: If user declines to specify after 2 attempts, fall back to "default" with warning: "Using generic dialogue — conversion effectiveness will be lower than type-specific scripts."
  3. Scene (11 presets or custom text) — default: modern_apartment

Round 2 (enhanced — use defaults if not stated):

  1. Model appearance: preset (9 templates) / body params / custom desc — default: asian_female_slim
  2. Realism (0-100) — default: 40
  3. Style: realism / pixar / anime_realistic — default: realism
  4. Dialogue style: natural / professional / enthusiastic — default: natural
  5. Camera: vlog / pro / static — default: vlog
  6. Target audience: auto / female / male — default: auto
  7. Duration (5-40s) — default: 10
  8. Language: zh / en — default: zh
  9. Task label (batch only)

Batch shortcut: If all tasks share config, ask once and apply to all. Only collect per-task differences.

Batch-Specific Recommendations

When batch mode selected, ADDITIONALLY show:

============================================================
Batch Mode — Additional Recommendations
============================================================

[REQUIRED] Specify exact garment type per task — do NOT use "default"
  WHY: Each garment type has 500+ chars of specialized dialogue with
  product-specific hand gestures (e.g., dress: pull hem to show fabric;
  pants: flip waistband to show grip strip). "default" loses all this.

[RECOMMENDED] Same gender per batch
  WHY: Mixing genders creates inconsistent dialogue tone — female uses
  filler words and emotional reactions, male is direct and factual.

[REQUIRED] Duration 10-15 seconds
  WHY: Under 5s cannot complete a product showcase. Over 15s triggers
  multi-segment auto-chaining which requires manual "extend" operations.
============================================================

Core Workflow

Step 0: Verify API Key (mandatory, never skip)

Platform-adaptive verification:

If bash/Python available (Claude Code, terminal):

import httpx
resp = httpx.get(f"{ARK_API_BASE}/api/v3/models",
                 headers={"Authorization": f"Bearer {ARK_API_KEY}"}, timeout=10)
# 200 -> proceed. 401/403 -> key invalid. Timeout -> network issue.

If no code execution (Claude.ai web, chat-only): Trust the user-provided key and proceed. Mark internally: api_verified: false. If Step 3 (image generation) fails with 401 -> surface the error then.

  • Key valid -> proceed to Step 1
  • Key invalid (401/403) -> report error, ask user to verify. Do NOT proceed.
  • No code execution -> proceed with unverified key, validate on first API call.

Single Mode

Step 1: Collect parameters (2 rounds max)
Step 2: Build model prompt (version-aware: 4.5 keyword / 5.0 natural language)
Step 3: Call Seedream API -> generate model image (720x1280, 9:16)
Step 4: Build Seedance prompt -> compose dialogue + actions + scene + camera
        Read references/dialogue-library.md for garment-specific scripts
        Read references/prompt-assembly.md for assembly rules
Step 5: Generate SOP
Step 6: If duration > 15s -> build chained multi-segment extend plan
Step 7: Validate output (see below)

Batch Mode

Step 0: Verify API key
Step 1: Collect batch size + per-task configs (2 rounds)
Step 2: Validate all configs (garment type != "default"?)
Step 3: For each task (sequential):
  a. Build model prompt
  b. Call Seedream API (if image needed)
  c. Compose dialogue (opening + core + closing) from dialogue-library.md
  d. Compose actions (garment-specific choreography)
  e. Assemble Seedance prompt
  f. If duration > 15s: build chained segments
  g. Generate SOP
  h. Mark task: completed / failed
Step 4: Validate all outputs
Step 5: Return results with progress summary

Progress: queued -> processing -> completed/failed
Partial success: batch completes even if some tasks fail.

Output Validation (mandatory, never skip)

Before delivering results, verify ALL:

  • [ ] Model image is 9:16 portrait with full body visible (head to feet)?
  • [ ] Prompt contains @image1 (garment) and @image2 (model ref)?
  • [ ] Dialogue matches the selected garment type (not generic "default")?
  • [ ] SOP specifies correct image upload order (image1=garment FIRST)?
  • [ ] If chained: every segment has continuation prompt + dialogue preview?
  • [ ] Brand constraint present: "Do not alter clothing pattern, color, texture or style"?

Any NO -> fix before delivering. Do NOT send unvalidated output.

Error Handling

FailureDetectionAction
No API keyARK_API_KEY empty or missingSTOP. Guide user to 火山方舟 console. Do NOT proceed.
Invalid API key401/403 from APIReport error. Ask user to verify key. Do NOT retry with guessed keys.
Seedream timeoutNo response in 300sRetry once with same prompt. Still fails -> report with the prompt used so user can try manually.
No image in responseAPI returns empty dataSimplify prompt (remove extras), retry. Still empty -> report error.
Batch task failsException during prompt assemblyMark task as failed with error message. Continue remaining tasks. Report partial results at end.
Invalid garment typeUser provides unknown typeMap to closest valid type or ask for clarification. Valid: dress/top/pants/jacket/suit/casual/default.

Degraded Mode: Prompt-Only (when image generation fails)

If Seedream API is unreachable or fails after retry, do NOT block the entire workflow. Skip image generation, still deliver prompt + SOP. Mark output clearly:

[Note] Model image generation unavailable (API error). Prompt and SOP generated successfully.
Use your own model photo as @image2 when operating on the Jimeng platform.

This ensures the user gets the valuable prompt + SOP even without the AI-generated model image.

Usage Example

Input: "帮我做一个女性穿搭视频,裙子类型,现代公寓场景"

Resolved params: gender=female, garment=dress, scene=modern_apartment, realism=40, style=realism, dialogue=natural, camera=vlog, audience=auto->female, duration=10, lang=zh

Output 1 — Model Image: 720x1280 PNG (asian_female_slim preset, realism=40)

Output 2 — Seedance Prompt:

一位面容和身材参考@图片2的年轻女性穿着@图片1中的服装,在简约现代的白色公寓客厅中,自然光从落地窗照入。她面朝镜头表情生动自然地展示服装,右手拉起裙摆展示面料(始终用右手),右手翻开裙摆内侧展示车线做工,小幅转身让裙摆飘动,右手捏腰部展示松紧设计,对着镜头说:「姐妹们你们快看...哇,不是,我真的没想到这条裙子上身效果这么好。你看这个面料,是那种...嗯...醋酸缎面的...(右手轻轻拉起裙摆展示)滑滑的凉凉的,而且有一定的厚度,不是那种廉价的薄纱感。然后你看这个车线...(右手翻开裙子内侧给镜头看)全部是包边走线的,没有毛边,做工真的很扎实。裙摆是A字的微微伞摆,你看我转一下...(转了一圈)你看它飘起来那个弧度,而且腰线这里有一个隐藏的松紧设计...(右手捏了捏腰部)不会勒但又收腰。你们猜多少钱?不到两百!超显腿长,闭眼入。」语气自然亲切,像在跟闺蜜视频通话。说话有停顿、有喘息、偶尔磕巴自我纠正,真实感强。Do not alter clothing pattern, color, texture or style. 手持vlog镜头感,竖屏9:16构图。音频要求:全程只有模特一个人的清晰人声,不出现第二个人的声音或对白。背景有符合场景的自然环境音,音量不超过人声的10%。视觉要求:全程保持中景到中近景,不要切到手部或脚部的特写镜头,避免手指变形问题。模特展示服装细节时始终使用右手操作,避免左右手切换导致的镜像翻转。全程画面中只有模特一人,不出现其他人物。

Output 3 — Operator SOP: Step-by-step for 即梦 platform (upload order, settings, quality checklist)

Domain Knowledge Role Declaration

The reference files contain dialogue scripts, model presets, API specs, and prompt templates. Their role is to assist prompt assembly — providing the raw materials that get composed into Seedance prompts. They do NOT replace the execution workflow. Never output reference content directly as the final answer. Always assemble through the workflow: collect params -> build prompt -> validate -> deliver.

References

FilePurposeWhen to read
references/model-presets.md9 model presets, body params, 17-level realism anchors, scene/camera/style presetsStep 2: building model prompt
references/seedream-api.mdSeedream 4.5/5.0 API endpoint, request format, cost, crop logicStep 3: calling API
references/prompt-assembly.mdPrompt composition order, multi-segment chaining constants, SOP templatesStep 4-6: assembling prompt and SOP
references/dialogue-library.mdComplete dialogue scripts: 7 garment types x 2 genders x 2 languages (28 scripts total), openings, closings, actionsStep 4: composing dialogue content

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

平台分布

OpenClaw

74.5%
按下载量换算719

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills