Ark Video Storyboard

Turn a scene idea into a structured video plan, then optionally execute it with the Ark video generation API.

This skill is confirmation-first:

• - First generate storyboard + prompts
• Let the user review and revise
• Only generate video after explicit user approval

Workflow

1. 1. 接收场景描述 — 用户描述视频场景（如"下班后去赛博朋克网吧打游戏"）
2. 询问参考图 — 用户描述场景后，主动询问："你有参考图吗？"（图片用于风格/人物参考）
3. 确认参考图角色 — 如果用户提供了参考图，询问："这张图是背景/风格参考还是人物形象参考？"

1. 4. 确认人物描述 — 如果有多个视频片段且没有人物参考图，主动询问用户："这个视频里主角的人物描述是什么？"（如"东亚男性、黑色短发、穿白色T恤"），收集后在每个段落提示词里保持完全一致
2. 生成脚本 — 展开场景为更丰富的整体脚本，拆分为多个连贯段落
3. 输出分镜 — 每个段落包含：参考图用途说明、人物描述（多段一致）、画面描述，光照状态、连贯性备注、英文 AI 提示词（含参考图风格描述+一致的人物描述）
4. 用户确认 — 展示分镜给用户确认："这是不是你要的脚本/提示词？"
5. 修改 — 用户如需调整（风格、节奏、镜头语言、人物细节、提示词措辞），修改后重新展示
6. 执行确认 — 用户确认后，询问"是否开始生成视频？"
7. 提交 API — 用户明确说"可以/开始生成"后，提交给 Ark API，逐段轮询结果，下载视频
8. 合并并发送 — 所有片段下载完成后，用 ffmpeg 合并为一个完整视频，检查大小（飞书限制约 20MB），必要时压缩，通过飞书发送给用户

视频合并与发送流程

所有片段下载完成后，按以下步骤合并并发送给用户：

第一步：定位片段目录

Ark API 下载的视频片段默认保存在 ~/.openclaw/media/{timestamp}/，按时间戳组织。确认目录存在：

CODEBLOCK0

第二步：合并视频

1. 1. 创建片段列表文件

CODEBLOCK1

seg 序号与片段数量一致，逐行追加。

1. 2. 执行合并

CODEBLOCK2

1. 3. 验证

CODEBLOCK3

第三步：检查大小并压缩（如需要）

飞书直接发送限制约 20MB：

• - ≤20MB：直接使用 INLINECODE1
• >20MB：压缩后再发

CODEBLOCK4

第四步：发送至飞书

使用 message 工具发送文件：

• - filePath: INLINECODE4
• INLINECODE5: INLINECODE6
• INLINECODE7: 告知用户视频已合并完成，共多少片段，时长多少

第五步：更新工作流记录

在 ~/.openclaw/workspace/WORKFLOW.md 中记录本次处理信息（时间戳、片段数量、输出文件路径、文件大小）。

人物一致性规则（关键）

如果视频有多个片段，且用户没有提供人物参考图，则：

• - 在步骤4中主动询问人物描述
• 在每个段落的提示词里保持完全相同的人物描述（外貌、发型、着装等措辞必须一字不差）
• 人物描述格式示例：INLINECODE9

如果用户提供了人物参考图，则每个提示词里统一写：INLINECODE10

Interaction Phases

Phase 1: Script / Prompt Confirmation

• - User gives the scene, style, references, and goal.
• If images are provided, first confirm whether each one is a background/environment reference or a character/subject reference.
• If multiple segments and no character reference image, ask for a consistent character description.
• Generate the storyboard, segment plan, and English prompts first.
• Ask the user whether this version is correct.
• If the user asks to tweak tone, pacing, camera language, subject details, prompt wording, or image-role interpretation, revise and show the updated version again.
• Do not call the Ark API in this phase unless the user explicitly asks for direct generation.

Phase 2: Execution Confirmation

• - After the user confirms the script/prompt is correct, ask whether to start generation if they have not already made that explicit.
• Only run the API submission / polling / download flow after explicit approval.
• If submission fails, immediately report the exact stage and error.

Input Requirements

Collect as many of these as possible before writing prompts:

• - Reference image or images（主动询问用户是否有参考图）
• Scene description
• Subject or product
• Target style (cinematic, cozy, commercial, dreamy, realistic, etc.)
• Intended use (ad, social clip, atmosphere film, storytelling, product demo)
• Constraints such as camera language, pacing, lighting, or ending mood
• Total duration target
• Segment count target
• Consistent character description（多段无人物参考图时必须收集）

If inputs are incomplete, still proceed with reasonable defaults and clearly state the assumptions.

Hard Rules

• - Default all human characters to East Asian / 东方亚洲人 unless the user explicitly specifies otherwise.
• All segments must belong to the same video, not unrelated clips.
• Maintain continuity for character appearance, wardrobe, environment, props, lighting logic, and emotional progression.
• Write the planning fields in Chinese unless the user requests another language.
• Write the final generation prompts in English unless the user explicitly wants Chinese prompts.
• Prefer cinematic, visual, action-oriented prompts over abstract descriptions.
• Do not silently retry failed API submissions in the background without telling the user.

Segment Output Format

Follow the schema in references/storyboard-schema.md.

At minimum include:

• - Segment index
• Duration seconds
• Character description (same across all segments)
• Visual description
• Lighting state
• Continuity notes
• English AI prompt (includes consistent character + reference style)

Prompt Construction Rules

When writing a segment prompt, include the details that matter most for video generation:

• - Subject identity and appearance (consistent character description, same in every segment)
• Camera angle or shot type
• Motion or action
• Scene and environment
• Lighting and mood
• Pacing or motion quality
• Style words only when they improve consistency
• Reference image style description (if provided by the user, e.g., "in cyberpunk neon city style per reference image")
• For all segments of the same video: character description must be IDENTICAL

Sequence Design Rules

Use this narrative rhythm by default unless the user asks for a different structure:

• - Segment 1: establish subject, place, and mood
• Segment 2: deepen action or environment interaction
• Segment 3: push visual/emotional peak or transition
• Final segment: resolve, land, or fade out with a clear ending image

For more than 4 segments, insert additional deepen / transition beats while preserving continuity.

Duration / Segment Logic

This skill should support dynamic segment splitting.

Examples:

• - 60 seconds ÷ 4 segments = 15 seconds each
• 60 seconds ÷ 6 segments = 10 seconds each
• 60 seconds ÷ 12 segments = 5 seconds each

Current validated Seedance 1.5 Pro rule from user-confirmed testing:

• - duration must be an integer in the range [4, 12]

So before execution:

1. 1. Compute INLINECODE13
2. Ensure the result is an integer
3. Ensure the result is within 4~12
4. If not, stop and explain the issue to the user before submitting

API Execution

API key loading order for actual generation:

1. 1. Explicit wrapper argument if one is added later
2. Environment variable INLINECODE14
3. INLINECODE15 → INLINECODE16
4. Backward-compatible old format: INLINECODE17

If the user wants actual generation, read references/api.md and use the scripts:

• - scripts/build_storyboard.py to assemble structured segment data
• INLINECODE20 to sequentially submit segments, poll each task, collect video_url, and optionally download videos
• INLINECODE22 to submit one segment at a time
• INLINECODE23 to query a task once and extract INLINECODE24
• INLINECODE25 to poll until completion and return INLINECODE26
• INLINECODE27 to download a finished video_url to local storage

Submit segments sequentially, not in parallel, unless the user explicitly asks otherwise.

Current Known Ark Payload Requirements

Current known request requirements include:

• - INLINECODE29
• INLINECODE30 (first item is the text prompt)
• INLINECODE31
• INLINECODE32
• INLINECODE33
• Reference image: use {"type": "image_url", "image_url": {"url": "<data_uri or url>"}} in content array

Current validated model in this workspace:

• - INLINECODE35

Error Handling Rule

If API submission fails, returns any model / parameter / schema error, or returns no valid task_id:

• - Stop immediately
• Tell the user the exact failing segment and stage
• Show the key error message
• Explain which parameter or payload assumption most likely caused it
• Do not pretend generation is still running
• Do not continue to later segments

If API submission succeeds and returns a valid task_id:

• - Continue to the next segment by default without interrupting the user for each success
• Do not notify the user for each successful segment submission
• After all segments are successfully submitted, send one consolidated update that all tasks are in the Ark queue and generation is underway

Example Shape

A good segment should look like this:

• - 人物描述：东亚男性，黑色短发，白色T恤（所有段落一致）
• 参考图用途：背景/风格参考（温馨卧室，城市夜景窗外，暖色灯光）
• 画面描述：描述主体、动作、构图，环境变化
• 光照状态：明确亮度，主光、轮廓光、氛围变化
• AI 提示词：人物描述 + 镜头 + 动作 + 光线 + 情绪，提示词末尾加参考图风格描述

See references/examples.md for a concrete sleeping-scene example.

When To Read References

• - Read references/storyboard-schema.md before generating structured segments.
• Read references/prompt-rules.md when you need guardrails for prompt quality or continuity.
• Read references/api.md before building or submitting API payloads.
• Read references/examples.md when the user wants output that matches the example style.