Agent skill · Media & Video

video-script

对已完成分析的视频进行导演与剪辑策划,再写带时间戳的中文解说并校验。work_dir 已包含 agent_narration_brief.md 与 vlm_analysis.json 时使用。适用于故事方向、片段选择、画面/原声/旁白分工、 解说写作与复核。输入 work_dir 中的理解索引;输出 recap_story_plan.json、visual_audio_board.json、 cut 模式需要的 clip_plan.json,以及通过校验的 narration.json。触发词:解说词、写解说、视频旁白、 narration script、写稿、解说文案、剪辑思路、导演思路。

pitechen592★ · +23/wk · 2 repos on radarProfile →
claude-codeships scriptsMIT
Install
npx skills add worldwonderer/video-recap-skills --skill video-script --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 20
SKILL.md size: 6 KB
Bundled scripts: yes
Path: skills/video-script/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 423 · +23 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## 1. 定位 本技能负责:创作方向、画面/声音计划、旁白写作与校验。Agent 不是 JSON 填写器,而要依次扮演: 1. 导演 2. 故事编辑 3. 画面剪辑师 4. 声音/旁白编辑 5. 第一次观看的观众 Agent 先记录简洁决定,再写时间线产物。`validate.py` 负责对理解索引做机械校验;full 模式还会把旁白对齐到安静窗口。 下面的 `scripts/...` 均相对于本技能目录。若执行器从仓库根目录启动,请给脚本路径加上本技能的绝对目录。本技能不从其他技能目录读取参考文件或辅助脚本;外部输入只来自显式路径与 `work_dir` 产物。 ## 2. 读取素材并确认状态 首先阅读: - `work_dir/agent_narration_brief.md`:场景、时长、安静窗口与字数预算。 - `asr_writing_chunks.json`:长对白的写作分块

More from video-recap-skills
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About this skill
What does the video-script skill do?

对已完成分析的视频进行导演与剪辑策划,再写带时间戳的中文解说并校验。work_dir 已包含 agent_narration_brief.md 与 vlm_analysis.json 时使用。适用于故事方向、片段选择、画面/原声/旁白分工、 解说写作与复核。输入 work_dir 中的理解索引;输出 recap_story_plan.json、visual_audio_board.json、 cut 模式需要的 clip_plan.json,以及通过校验的 narration.json。触发词:解说词、写解说、视频旁白、 narration script、写稿、解说文案、剪辑思路、导演思路。

How do I install it?

Run `npx skills add worldwonderer/video-recap-skills --skill video-script --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From worldwonderer/video-recap-skills, a repository with 423 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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