HyperFrames Animation
heygen-com/hyperframes
Collects motion rules, scene blueprints, transitions and runtime adapters for HyperFrames video compositions, with GSAP as the default animation runtime.
整片视频产线（原片 → 包装级成片）：九步流程 + 八件质量门 + 两道人工确认门，产出成片与全套交付物. An agent skill from ZJU-REAL/Easel.
Install Video Production
$ npx skills add ZJU-REAL/Easel --skill video-production -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ZJU-REAL/Easel video-production --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/openclaw/video-production .claude/skills/video-production && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .claude/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-productionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ZJU-REAL/Easel --skill video-production -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ZJU-REAL/Easel video-production --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/openclaw/video-production .agents/skills/video-production && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .agents/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ZJU-REAL/Easel --skill video-production -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ZJU-REAL/Easel video-production --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/openclaw/video-production .cursor/skills/video-production && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .cursor/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ZJU-REAL/Easel.git --path skills/openclaw/video-production--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ZJU-REAL/Easel --skill video-production -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ZJU-REAL/Easel video-production --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/openclaw/video-production .gemini/skills/video-production && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .gemini/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ZJU-REAL/Easel video-productionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ZJU-REAL/Easel --skill video-production -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/openclaw/video-production .github/skills/video-production && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .github/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ZJU-REAL/Easel --skill video-production -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ZJU-REAL/Easel video-production --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/openclaw/video-production .opencode/skills/video-production && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "video-production" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/video-production into .opencode/skills/video-production/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "video-production", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
video-production- GitHub stars
- 3.4k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 261 words
- Files
- 110 (incl. scripts)
- Skills in repo
- 114
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
整片视频产线（原片 → 包装级成片）：九步流程 + 八件质量门 + 两道人工确认门，产出成片与全套交付物. An agent skill from ZJU-REAL/Easel.
- Works in 3 steps: tier1 现成稿（最优）：源片自带字幕/台词就用它——start… → tier2 云端 ASR API：没现成稿但配了… → tier3 本地 whisper（兜底）：都没有才用本地…
- Tasks that involve Video production
- SKILL.md covers 什么时候用, 快速开始, 交互循环（重要） and 命令一览, plus 3 more sections
- Runs Python scripts from its folder; calls python and bash; needs SILICONFLOW_API_KEY
What it does
Video Production is an agent skill from ZJU-REAL/Easel. 整片视频产线（原片 → 包装级成片）：九步流程 + 八件质量门 + 两道人工确认门，产出成片与全套交付物。 当用户说"用视频产线做一支整片""把这条原片做成片""整片包装""走视频产线"时使用。 全程经独立接口驱动：每步可核验、门不过不交付。 与兄弟技能分界：本 SKILL 的输入是已有的整条原片，做的是重包装（分场/动效/字幕/调色 + 质量门）， 过程重、需两次人工点头；从一句话主题无中生有出片用 auto-short-video； 手上只有一组图片用 slideshow-video；把长片切成多条短视频用 clipify 或 video-highlights。
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 115 other files, including scripts (for example `EASEL-META.md`, `scripts/video_pipeline.py` and `vendor/VENDOR.md`).
It sits in Media & Creative, covering Video production. The repository describes itself as: An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Video production
Example prompts
- “用视频产线做一支整片”
- “把这条原片做成片”
- “/video-production”
Requirements
- Python 3
- A credential in SILICONFLOW_API_KEY
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- tier1 现成稿（最优）：源片自带字幕/台词就用它——start --transcript 路径。.srt/.vtt 会自动转成段级 transcript.json（保留时间轴）；.json（segments 结构）直接用。Easel 做的口播剧一般自带…
- tier2 云端 ASR API：没现成稿但配了 SILICONFLOW_API_KEY（env）→ 自动调硅基流动（默认 XingChenAGI/XingChenGSR-V1.0，可用 SILICONFLOW_ASR_MODEL / SILICONFLOW_BASE_URL…
- tier3 本地 whisper（兜底）：都没有才用本地 large-v3（首次下约 3GB）。需 faster-whisper。
What it can do on your machine
Read from SKILL.md and the folder at commit 278f420. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
pythonbash
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
SILICONFLOW_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Video Production loads about 1.1k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 261 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from ZJU-REAL/Easel at commit 278f420, republished under its Apache-2.0 licence (© ZJU-REAL). 261 words, ~1,118 tokens.
Download SKILL.mdSave it as
.claude/skills/video-production/SKILL.md (or your agent's skills folder). This skill also uses 109 other files; get the full folder from GitHub.- name
- video-production
- description
- 整片视频产线（原片 → 包装级成片）：九步流程 + 八件质量门 + 两道人工确认门，产出成片与全套交付物。 当用户说"用视频产线做一支整片""把这条原片做成片""整片包装""走视频产线"时使用。 全程经独立接口驱动：每步可核验、门不过不交付。 与兄弟技能分界：本 SKILL 的**输入是已有的整条原片**，做的是重包装（分场/动效/字幕/调色 + 质量门）， 过程重、需两次人工点头；从一句话主题**无中生有**出片用 auto-short-video； 手上只有一组图片用 slideshow-video；把长片**切成多条**短视频用 clipify 或 video-highlights。
- layer
- produce
整片视频产线（video-production）
把一支原片（口播 / 独白）做成包装级成片：摸底 → 转录 → 分场 → 设计表 → 脚手架 → 写码 → 验证 → 预览 → 渲染 → 交付。质量不靠自觉，靠可执行的门。
产线 SDK 已内置在本技能
vendor/video-pipeline-sdk/（随 Easel 进仓、可复现、可在其基础上改）。 首次使用先跑一次依赖还原：bash <ROOT>/skills/openclaw/video-production/vendor/video-pipeline-sdk/deps/bootstrap.sh（装 Remotion 渲染引擎，--ignore-scripts；node_modules 不入库）。
什么时候用
用户说「用视频产线做一支整片 / 把这段素材做成片 / 整片包装」时使用。
开工前检查（缺源片不要动工）
- 源片必需：必须有可读的本地路径。用户没给 → 先向用户要（要路径，或提示他把文件拖进聊天 / 拷到内容库收件箱）；严禁用占位素材开工
- 主题与基调（
--brief）建议要一句；现成材料（转录稿 / 分场 / 设计表）有就给、没有就按流程走（流程会在需要时停下）
转录三级策略（选一个，优先级从上到下）
产线第二步要把口播里说的话转成带时间轴的文字稿。三级降级，越靠前越省：
- tier1 现成稿（最优）：源片自带字幕/台词就用它——
start --transcript 路径。.srt/.vtt会自动转成段级transcript.json（保留时间轴）；.json（segments 结构）直接用。Easel 做的口播剧一般自带 SRT，走这条即可，不下模型。 - tier2 云端 ASR API：没现成稿但配了
SILICONFLOW_API_KEY（env）→ 自动调硅基流动（默认XingChenAGI/XingChenGSR-V1.0，可用SILICONFLOW_ASR_MODEL/SILICONFLOW_BASE_URL覆盖）。key 只从环境变量读，勿写进命令/仓库。 - tier3 本地 whisper（兜底）：都没有才用本地 large-v3（首次下约 3GB）。需
faster-whisper。
让用户看得见（产物贴进对话 · 免上传）
对话消息直接支持图片与视频（站内媒体通道 /api/media/，零上传、零改前端）。产物落盘后，把它们贴进消息、再配卡片：
- 图片：Markdown 图片语法（
!+ 方括号说明文字 + 圆括号地址），地址写/api/media/<outputs 相对路径，逐段 URL 编码>（示例文件名：视频产线/<时间戳>/run/preview/f60.png） - 视频：
<video src="/api/media/<outputs 相对路径>" controls style="max-width:420px">标签 - 文件：Markdown 链接语法（方括号文字 + 圆括号地址）指向
/api/media/<outputs 相对路径>，或把要点直接摘进消息
三处必用：
- 设计表确认卡之前：先贴设计表要点摘要 + 全文链接（用户"看得见才审得动"）
- 预览确认卡之前：把
run/preview/*.png逐张贴成图片，再出预览卡 - 交付时：成片贴成 video 标签（
视频产线/<时间戳>/out/final.mp4），附门报告链接
素材怎么给（用户问"怎么把视频给你"时这样答）
- 首选 · 本地路径：文件放本机任意位置，对话里报路径即可（例：
E:/clips/raw.mp4）。无大小限制、不复制文件 - 小文件可直接拖进聊天上传（进内容库收件箱）；大文件不走上传——直接报本地路径（见第 1 条）
- 也可先手动拷进
outputs/_inbox/再报路径
快速开始
python <ROOT>/skills/openclaw/video-production/scripts/video_pipeline.py doctor
python <ROOT>/skills/openclaw/video-production/scripts/video_pipeline.py start --source "C:/path/raw.mp4" --brief "主题一句话"start 依次做：建运行态 → 机械段（摸底 / 转录 / 分场）→ 停在需要人参与的地方。
交互循环（重要）
每个命令最后一行是 STATE: ...：
| STATE | 含义 | 你要做的 |
|---|---|---|
awaiting-answer | 有题待作答 | pending 读题 → 用 ask_user 工具转问用户 → answer + resume |
done | 全流程完成 | 报告产物路径（见下） |
gate-failed | 质量门失败 | 把失败项如实报告，不要交付 |
error | 异常 | 把错误原文报告用户 |
转问用户（ask_user 映射规则）
- ask_user 限制：一次 1–3 问、每题 2–4 个选项、header ≤12 字——按此裁剪，选项 label 用中文原样
- 收到回答后，把用户所选 label 对照问题 JSON 的
options[].value映射回：
| 问题 id | 选项 label → value |
|---|---|
| checkpoint-1（设计表确认） | 通过，按设计表开工→approve ｜ 带意见修改→revise ｜ 打回重做→reject |
| checkpoint-2（预览确认） | 通过，渲全片→approve ｜ 有场次要改→revise |
- 写回答并续跑：
python <ROOT>/skills/openclaw/video-production/scripts/video_pipeline.py answer --id checkpoint-1 --values approve --notes "可选备注"
python <ROOT>/skills/openclaw/video-production/scripts/video_pipeline.py resume自由输入题（如 need-design-table）
题目会写明要产出的文件与放置位置。把说明转给用户；文件就位后重新 resume（自动检测在档）。
开工时已有设计表的话，start 直接加 --design-table <md 路径>。
命令一览
| 命令 | 用途 |
|---|---|
doctor | 环境自检（SDK 路径 / 依赖 / 版本） |
start --source ... [--brief] [--transcript] [--scenes] [--config] [--gates] [--design-table] | 开工，跑到第一个停点 |
pending | 打印待作答问题（JSON） |
answer --id ... --values a,b [--notes ...] | 写入作答 |
resume | 从停点续跑 |
status | 进度 / 待作答 / 路径 |
所有命令支持 --run-dir（默认最近一次 start）、--base（运行态根）、--sdk（SDK 路径；默认用内置 vendor/video-pipeline-sdk，也可用 --sdk/环境变量 VIDEO_PIPELINE_SDK 覆盖）。
--gates 可带质量门清单 JSON（内部支持 {run_dir} / {out_dir} 占位符自动替换）。
产物
默认运行态在 <工作区>/outputs/视频产线/<时间戳>/（交付物进「视频产线」项目，内容库里可见）：
run/：run-state、questions / answers、checkpoints、gate-report、logsout/：final.mp4、design-table.md、gate-report.md/gate-report.json、manifest.json
红线
- 只转发，不复制 SDK 逻辑；SDK 升级不改本技能
- 门不过不交付；任何 FAIL 必须如实报告
- 写长代码/大文件务必分块写（单次输出有上限，被截断会中断任务；分 2-4 段续写）
- 交付自动带人审包（
review-pack/：每场定格帧 + 核对表）；把它贴给用户，照单核对（无视觉的执行者靠人眼兜底） - 设计表是创作步：与用户确认后产出，机器只校验在档
退出码（机器语义）
0 完成 ｜ 2 门失败 ｜ 3 待作答 / 待审批 ｜ 1 异常
© ZJU-REAL, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 109 other files (scripts) in skills/openclaw/video-production of ZJU-REAL/Easel.
- SKILL.md
- EASEL-META.md
- scripts/video_pipeline.py
- vendor/VENDOR.md
- vendor/video-pipeline-sdk/.gitattributes
- vendor/video-pipeline-sdk/.gitignore
- vendor/video-pipeline-sdk/ATTRIBUTIONS.md
- vendor/video-pipeline-sdk/CHANGELOG.md
- vendor/video-pipeline-sdk/INTERFACE.md
- vendor/video-pipeline-sdk/LICENSE
- vendor/video-pipeline-sdk/PITFALLS.md
- vendor/video-pipeline-sdk/README.md
- vendor/video-pipeline-sdk/VERSION
- vendor/video-pipeline-sdk/assets/cards/index.html
- vendor/video-pipeline-sdk/assets/fonts/MaShanZheng-Regular.ttf
- … and 95 more
Open the folder on GitHubat commit 278f420
Compare with similar skills
Video Production next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Video Production this skillZJU-REAL/Easel | 3.4k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| HyperFrames Animationheygen-com/hyperframes | 60k | 3 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Stitch to Remotion Walkthrough Videosgoogle-labs-code/stitch-skills | 8.5k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 | |
| Faceless Explainer Videoheygen-com/hyperframes | 60k | 3 repos | ~7.7k | Automated safety check: Notes | Apache-2.0 | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 | |
| Video ShotcraftVincentwei1021/video-shotcraft | 11k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 |
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- Official
Stitch to Remotion Walkthrough Videos
google-labs-code/stitch-skills
Builds walkthrough videos from Stitch design projects using Remotion, with transitions, zoom effects and text overlays on each screen.
Faceless Explainer Video
heygen-com/hyperframes
Turns an article, notes or a topic brief into an explainer video whose visuals are invented per scene, built frame by frame in HyperFrames with no footage.
Video Understand
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
Video Shotcraft
Vincentwei1021/video-shotcraft
Makes cinematic product videos with Remotion from shot recipe cards, a ready template, real page screenshots, camera moves and sound design, or builds a single animated shot.
Figma to HyperFrames
heygen-com/hyperframes
Imports Figma assets, brand tokens, components and motion into a HyperFrames video composition, using the Figma REST API with a connector or native export for shaders.
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微信公众号文章排版引擎：把 Markdown / Word(.docx) / PDF / 纯文本转成可直接粘贴进公众号编辑器的 HTML，自动章节编号、关键词标记、引言卡、目录、代码块、图片/GIF、作者签名；主题从 references/theme-index.md…
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微信公众号文章自动创作与发布工具。给定参考文章、文字或文档，自动搜索整理全网相关信息、生成图文并茂的公众号文章，并发布到微信公众号草稿箱。特别强调反 AI 检测写作。
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社媒卡片视觉设计系统：提供配色、中文字体层级、满画幅布局、品类骨架和死空白/密度质检，避免模板化 PPT 与廉价 AI 感。
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将数据或文字内容转化为可视化信息图，支持静态（AntV）和动画 GIF 两种模式。当用户需要制作信息图、数据可视化、流程图、对比图、动画图表、GIF 图表、思维导图、SWOT 分析图时调用。本地渲染信息图/GIF 动画；要单张静态图片 URL 用 chart-visualization，要 CSV/JSON→整页报告用 data-report
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Questions about Video Production
What does Video Production do?
整片视频产线（原片 → 包装级成片）：九步流程 + 八件质量门 + 两道人工确认门，产出成片与全套交付物. An agent skill from ZJU-REAL/Easel. Video Production is an agent skill from ZJU-REAL/Easel.
When should I use Video Production?
Video Production fits situations like: tasks that involve Video production.
How do I install Video Production in Claude Code?
Run `npx skills add ZJU-REAL/Easel --skill video-production -a claude-code`. Or copy the skill folder (skills/openclaw/video-production in ZJU-REAL/Easel) into .claude/skills/video-production in your project. Claude Code loads it when a task matches its description.
How do I install Video Production in Codex?
Run `npx skills add ZJU-REAL/Easel --skill video-production -a codex`. Or copy the skill folder (skills/openclaw/video-production in ZJU-REAL/Easel) into .agents/skills/video-production in your project. Codex loads it when a task matches its description.
Can I use Video Production in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ZJU-REAL/Easel --skill video-production -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/video-production, .gemini/skills/video-production, .github/skills/video-production and .opencode/skills/video-production in your project.
What does Video Production need to run?
Going by SKILL.md and its folder, Video Production needs Python for the scripts in its folder, the command-line tools its instructions call (python and bash) and credentials named SILICONFLOW_API_KEY. Our summary lists: Python 3; A credential in SILICONFLOW_API_KEY.
Does Video Production access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Video Production safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Video Production use?
Video Production is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Video Production use?
About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Video Production?
Skills that share tags, products or a category with Video Production: HyperFrames Animation (heygen-com/hyperframes, 60k stars), Stitch to Remotion Walkthrough Videos (google-labs-code/stitch-skills, 8.5k stars), Faceless Explainer Video (heygen-com/hyperframes, 60k stars) and Video Understand (calesthio/OpenMontage, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Video Production?
ZJU-REAL (a GitHub organization) maintains it in ZJU-REAL/Easel, which has 3,376 GitHub stars. The repository holds 114 skills in this directory. The repository was last updated on October 9, 2026.
Source: ZJU-REAL/Easel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.