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Agent Skill · 效率

chain-referenced-shortform-video(链引用短视频)

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。

chain-referenced-shortform-video 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 6,396。

总安装 9,425周安装 385GitHub Stars 公开资料未说明下载 3,049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
0.2.1

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:chain-referenced-shortform-video(链引用短视频)
来源仓库:https://github.com/hakityc/chain-referenced-shortform-video
安装命令:
openclaw skills install chain-referenced-shortform-video
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 chain-referenced-shortform-video

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

支持跨镜头连续性与电影语言的视频生成与故事板制作。适用于短片、动画序列与 Remotion 项目开发的素材组织。通过 clawhub 安装并使用 openclaw skills install chain-referenced-shortform-video 命令集成。需确认分辨率、时长与素材版权合规性,避免法律风险。

建议结合来源仓库和 README 了解渲染管线与外部资源引用规则。

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 chain-referenced-shortform-video;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

chain-referenced-shortform-video 怎么安装?

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

chain-referenced-shortform-video 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。

chain-referenced-shortform-video 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

chain-referenced-shortform-video 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。

chain-referenced-shortform-video 用的人多吗?

公开数据是累计安装 9,425 次,近一周安装 385 次,下载 3,049 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。

chain-referenced-shortform-video 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
chain-referenced-shortform-video

链引用短视频 · 本页

9,425—只读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
chain-referenced-shortform-video
description
Use when generating AI films, short dramas, cinematic sequences, or storyboard-driven video scenes that need strong cross-shot continuity and real film-language control. Covers asset-driven preproduction, shot lists, storyboards, blocking, lensing, camera movement, five-dimension prompt control, subtractive prompting, staged keyframe gates, bridge-frame selection, shot cards, continuity ledgers, and chain-referenced video generation. Trigger for requests about AI movie generation, cinematic prompt engineering, short drama workflows, continuity pipelines, previsualization, scene packs, shot templates, bridge frames, or swapping scripts without rewriting the workflow.

Chain-Referenced Shortform Video

Use this skill when the user wants to generate AI movies, short dramas, or cinematic scene sequences that hold character, scene, prop, and film-language continuity across multiple shots.

What to load first

Read only these files first:

  • references/film-language.md
  • references/review-rubric.md
  • references/repo-mapping.md

Load project-specific implementation files only if the user needs them.

For this repository, then load:

  • /Users/lebo/project/ai-video/src/ai_video_control/models.py
  • /Users/lebo/project/ai-video/src/ai_video_control/shortform.py
  • /Users/lebo/project/ai-video/src/ai_video_control/review.py
  • /Users/lebo/project/ai-video/src/ai_video_control/cli.py

Operating stance

Act as:

  • continuity supervisor
  • storyboard artist
  • cinematographer
  • edit-minded prompt designer

Do not treat the task as write a prettier prompt. Treat it as preproduction -> gated keyframes -> chained shots.

Core rules

  1. Start with single-scene micro-stories.
  2. Model each scene and shot with five dimensions:

- subject_motion - environment_light - medium_rendering - temporal_state - camera_optics

  1. Use subtractive prompting:

- the master-scene prompt defines the locked facts - shot-delta prompts describe only the allowed change - never restate identity, wardrobe, room layout, or lighting if already locked

  1. Do not render final sequence clips unless:

- the master scene passes gate - the shot-delta keyframe passes gate

  1. For shot n > 1, use chain reference:

- select a bridge frame from the tail of video n-1 - use that bridge frame as first_frame - use the approved shot n keyframe as last_frame

  1. Every shot must also be readable as cinema:

- clear dramatic beat - clear blocking - intentional framing - intentional camera movement - intentional edit relationship to the previous shot

Production model

Design each shot as eight layers:

  1. dramatic purpose
  2. emotional state
  3. subject blocking
  4. screen geography
  5. shot size / angle / lens intent
  6. camera movement
  7. light / atmosphere continuity
  8. edit seam to previous and next shot

If these layers are not explicit, prompting will drift because the model will improvise them.

Recommended asset model

Create reusable inputs before writing prompts:

  1. character bible
  2. scene pack
  3. prop pack
  4. shot template
  5. beat sheet
  6. continuity ledger
  7. episode spec

Keep them loosely coupled so you can swap scripts or settings without rewriting the workflow.

Production order

  1. Build a character bible with only core identity anchors.
  2. Build a scene pack that locks layout, lighting, and camera baseline.
  3. Build a prop pack that separates:

- fixed props - allowed temporal changes - forbidden drift

  1. Build a beat sheet that states for each shot:

- dramatic purpose - emotional change - what the viewer must learn or feel - what must be visible for the next cut to work

  1. Build a shot template that locks:

- framing - lens intent - camera side of line - floor marks - blocking rules - allowed changes - forbidden changes

  1. For each shot, write a concise shot card with:

- shot size - angle - movement - blocking - screen direction - bridge-frame preference - forbidden composition

  1. Generate master-scene candidates.
  2. Gate the master scene for:

- clarity - identity - scene stability - prop stability - cinematic readability

  1. Generate shot-delta candidates from the approved master scene.
  2. Gate each shot-delta candidate for:

- identity - scene - props - camera - staging readability - edit compatibility

  1. Generate a short clip for the approved shot.
  2. Extract tail frames and select the best bridge frame.
  3. Use the bridge frame to condition the next shot.
  4. Update the continuity ledger after every approved shot.

Shot design rules

Each shot should usually change only one major thing:

  • subject pose or performance beat
  • camera distance
  • camera movement
  • temporal state
  • prop interaction

Do not change all of them at once.

Prefer this progression:

  • establish
  • orient
  • develop
  • payoff
  • exit or bridge

If a scene feels flat, vary shot size or movement. If a scene feels unstable, reduce simultaneous changes.

How to write prompts

Master scene prompt

Include:

  • core protagonist identity
  • scene layout and lighting
  • fixed props
  • framing and floor marks
  • camera side of line
  • baseline lens feeling
  • baseline temporal state

Do not include:

  • later shot deltas
  • multiple unrelated actions
  • optional accessories unless they are essential continuity anchors

Shot-delta prompt

Include only:

  • the allowed action change
  • the allowed temporal change
  • the blocking delta
  • the camera delta if and only if it is allowed
  • the intended audience read of the shot
  • explicit continuity constraints such as:

- same framing - same side of line - same floor marks - no new props - no room changes

Do not include:

  • full face or wardrobe re-description
  • full scene re-description
  • multiple new props
  • camera reinvention unless camera change is explicitly allowed

Camera and blocking heuristics

  • If the emotional beat is intimate, bias toward CU / MCU, restrained blocking, and minimal movement.
  • If the beat is spatial or tactical, bias toward MS / LS / WS and clear geography.
  • Use push-in for realization, pressure, or dread.
  • Use pull-back for alienation, aftermath, or loss.
  • Use lateral track when the subject is moving through space.
  • Use handheld only when instability is part of the intended feeling.
  • Preserve screen direction unless the cut is motivated.
  • Do not cross the 180-degree line by accident.
  • When in doubt, simplify the move before simplifying the art direction.

What to gate

Master scene gate

Fail if:

  • the image is soft or artifacted
  • the subject identity is unstable
  • the room layout drifts
  • fixed props are missing
  • lighting is inconsistent with the pack
  • the frame does not establish usable geography
  • the shot feels compositionally dead or confusing

Shot-delta gate

Fail if:

  • the character changes outside the allowed delta
  • layout drifts
  • props move outside the whitelist
  • framing changes without permission
  • the shot spec contradicts itself
  • blocking becomes unclear
  • screen direction breaks without a motivated transition
  • camera movement conflicts with the beat
  • the shot cannot cut cleanly from the previous shot

Bridge-frame gate

Select from the tail of the previous clip based on:

  • face visibility
  • pose stability
  • prop completeness
  • low motion blur
  • continuity usefulness
  • edit seam quality
  • pose that can plausibly launch the next action

Do not use the literal last frame by default.

Good defaults

  • shot length: 3-5s
  • master scene candidates: 4
  • shot-delta candidates per shot: 3
  • bridge-frame tail window: final 20%
  • bridge-frame candidates: 6
  • frame gate should prefer passing candidates over merely high scores

Review loop

After every approved shot, record:

  • what changed
  • what remained locked
  • what made the shot pass
  • what phrase or move caused drift
  • which bridge frame is canonical for the next shot

This ledger is more important than preserving every old prompt.

Fallback strategy

If image-to-image editing is unavailable:

  1. use text-to-image for the master scene
  2. use image-to-video draft clips for shot-delta search
  3. extract candidate frames
  4. gate those frames as shot-delta keyframes

This is slower, but often more reliable than returning to freeform text-only keyframe generation.

Borrow and adapt, do not copy blindly

Useful patterns from other ecosystems:

  • storyboard skills: shot vocabulary, 180-degree rule, panel annotations
  • cinematic writing skills: lighting, lens, and color language
  • video production skills: feedback loops, approval ledgers, revision discipline
  • Seedance-specific skills: explicit reference roles and time segmentation

Do not import one common bad habit from generic cinematic skills:

  • repeating the full identity and set description in every shot prompt

For this workflow, that causes prompt pollution and continuity drift.

Repo mapping

When applying this skill to this repository, map film-language concepts into the current episode YAML through references/repo-mapping.md.

What to fix first when continuity fails

  • If identity drifts: reduce identity anchors to the most visible features.
  • If layout drifts: strengthen the scene pack and reduce motion.
  • If props drift: move them into allowed_changes or remove them from the shot text.
  • If framing drifts: add explicit same framing / same floor mark constraints to the video prompt.
  • If eyelines or geography fail: fix the shot card and side-of-line rule before touching model settings.
  • If the shot feels uncinematic: fix shot size, movement, and blocking before adding more adjectives.
  • If a cut feels bad: change the bridge frame, not the character description.
  • If the spec is self-contradictory: fix the spec first, not the prompt.

平台分布

OpenClaw

70.69%
按下载量换算2,155

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

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