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ark-video-storyboard方舟视频故事板

Agent Skill

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。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:ark-video-storyboard(方舟视频故事板)
来源仓库:https://github.com/yunni123/ark-video-storyboard
安装命令:
openclaw skills install ark-video-storyboard
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。

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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 ark-video-storyboard

简介

从场景描述或参考图像生成视频故事板和提示词。

  • 支持多段视频生成前的脚本确认与分镜设计。ark-video-storyboard 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 可与用户交互确认内容方向后再提交生成任务。
  • 安装命令:openclaw skills install ark-video-storyboard。
  • 需确保输入内容清晰,避免模糊描述影响生成效果。

SKILL.md

name
ark-video-storyboard
description
Generate a storyboard and prompts from a scene or reference images, confirm the script with the user, then optionally submit multi-segment video generation tasks to the Volcengine Ark video API. Use when the user wants to turn a scene idea into a structured video workflow, especially for mood films, product scenes, narrative shorts, or image-to-video prompt pipelines.

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. 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?"

- 背景/风格参考:作为环境、色调、氛围的视觉基准 - 人物形象参考:作为主角外貌、着装、动作的基准

  1. 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:

ls ~/.openclaw/media/{timestamp}/seg*.mp4

第二步:合并视频

  1. 创建片段列表文件
cd ~/.openclaw/media/{timestamp}/
echo "file 'seg1.mp4'\
file 'seg2.mp4'\
..." > concat.txt
seg 序号与片段数量一致,逐行追加。
  1. 执行合并
ffmpeg -f concat -safe 0 -i concat.txt -c copy merged.mp4
  1. 验证
ls -lh merged.mp4
ffprobe -v quiet -print_format json -show_format merged.mp4

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 merged.mp4
  • >20MB:压缩后再发
ffmpeg -i merged.mp4 \
  -c:v libx264 \
  -crf 28 \
  -c:a aac \
  -b:a 128k \
  -y merged_compressed.mp4

第四步:发送至飞书

使用 message 工具发送文件:

  • filePath: ~/.openclaw/media/{timestamp}/merged_compressed.mp4
  • channel: feishu
  • message: 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

~/.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
  • 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:East Asian young man, black short hair, white T-shirt, 25 years old

如果用户提供了人物参考图,则每个提示词里统一写:consistent with the character in reference image

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. Compute duration = total_duration_seconds / segment_count
  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. Explicit wrapper argument if one is added later
  2. Environment variable ARK_API_KEY
  3. ~/.openclaw/openclaw.jsonskills.entries.ark-video-storyboard.apiKey
  4. Backward-compatible old format: skills.ark-video-storyboard.apiKey

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

  • scripts/build_storyboard.py to assemble structured segment data
  • scripts/run_full_generation.py to sequentially submit segments, poll each task, collect video_url, and optionally download videos
  • scripts/submit_segment.py to submit one segment at a time
  • scripts/get_task_result.py to query a task once and extract video_url
  • scripts/poll_task_until_done.py to poll until completion and return video_url
  • scripts/download_video.py 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:

  • model
  • content (first item is the text prompt)
  • ratio
  • duration
  • watermark
  • Reference image: use {"type": "image_url", "image_url": {"url": "<data_uri or url>"}} in content array

Current validated model in this workspace:

  • doubao-seedance-1-5-pro-251215

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.

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