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:
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API Configuration — Mandatory Recommendations
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[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.
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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):
- Model gender (female/male) — default: female
- 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."
- Scene (11 presets or custom text) — default: modern_apartment
Round 2 (enhanced — use defaults if not stated):
4. Model appearance: preset (9 templates) / body params / custom desc — default: asian_female_slim
5. Realism (0-100) — default: 40
6. Style: realism / pixar / anime_realistic — default: realism
7. Dialogue style: natural / professional / enthusiastic — default: natural
8. Camera: vlog / pro / static — default: vlog
9. Target audience: auto / female / male — default: auto
10. Duration (5-40s) — default: 10
11. Language: zh / en — default: zh
12. 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:
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Batch Mode — Additional Recommendations
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[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.
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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:
Any NO -> fix before delivering. Do NOT send unvalidated output.
Error Handling
| Failure | Detection | Action |
|---|
| No API key | ARK_API_KEY empty or missing | STOP. Guide user to 火山方舟 console. Do NOT proceed. |
| Invalid API key | 401/403 from API | Report error. Ask user to verify key. Do NOT retry with guessed keys. |
| Seedream timeout | No response in 300s | Retry once with same prompt. Still fails -> report with the prompt used so user can try manually. |
| No image in response | API returns empty data | Simplify prompt (remove extras), retry. Still empty -> report error. |
| Batch task fails | Exception during prompt assembly | Mark task as failed with error message. Continue remaining tasks. Report partial results at end. |
| Invalid garment type | User provides unknown type | Map 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
| File | Purpose | When to read |
|---|
| references/model-presets.md | 9 model presets, body params, 17-level realism anchors, scene/camera/style presets | Step 2: building model prompt |
| references/seedream-api.md | Seedream 4.5/5.0 API endpoint, request format, cost, crop logic | Step 3: calling API |
| references/prompt-assembly.md | Prompt composition order, multi-segment chaining constants, SOP templates | Step 4-6: assembling prompt and SOP |
| references/dialogue-library.md | Complete dialogue scripts: 7 garment types x 2 genders x 2 languages (28 scripts total), openings, closings, actions | Step 4: composing dialogue content |