video-recap

video-recap is a skill for Claude Code from zenstory-ai/video-recap-skills. It costs 128 tokens per session (3,619 once invoked), scanned A, original, MIT.

An end-to-end workflow for turning a video into a Chinese narrated recap. It coordinates video analysis, story planning, editing, voice generation, and final audio and subtitle assembly.

In plain words
What is it for?
Use it for narrated summaries of films, television, documentaries, short dramas, educational videos, and other MP4, MOV, MKV, or WebM files.
Why use it?
It connects the separate stages of making a recap so their files and timing information can be reused when work is resumed.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 tools/measure_subtitle.py <video>.

Part of the video-recap-skills plugin — 6 skills shipped together

Good fit Use it for narrated summaries of films, television, documentaries, short dramas, educational videos, and other MP4, MOV, MKV, or WebM files.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/zenstory-ai/video-recap-skills
agentmods
npx agentmods add skills/zenstory-ai/video-recap-skills/video-recap

Made for: Claude Code.

Or install video-recap-skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for video-recap

README.md
[![agentmods](https://agentmods.dev/badge/skills/zenstory-ai/video-recap-skills/video-recap/github.svg)](https://agentmods.dev/skills/zenstory-ai/video-recap-skills/video-recap)
Your own site
<a href="https://agentmods.dev/skills/zenstory-ai/video-recap-skills/video-recap"><img src="https://agentmods.dev/badge/skills/zenstory-ai/video-recap-skills/video-recap/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for video-recap

Your own site · 80×15
<a href="https://agentmods.dev/skills/zenstory-ai/video-recap-skills/video-recap"><img src="https://agentmods.dev/badge/skills/zenstory-ai/video-recap-skills/video-recap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 128 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,619 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00128 $0.03619
Opus 5 $0.00064 $0.01809
Sonnet 5 $0.00026 $0.00724
Haiku 4.5 $0.00013 $0.00362

Measured 12d ago against content hash 217913bc6f9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

video-recap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 21 executable files (scripts/doctor.py, scripts/final_qc.py, scripts/lib.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/video-recap/SKILL.md · 217 lines

How it starts

The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.

1. 定位与流程

本技能是五个独立技能的轻量编排器。各技能只通过 work_dir 中的 JSON / MP4 产物通信,不共享代码:

video-understanding ─▶ Agent 按 video-script 制定方案并写稿 ─▶ [video-cut] ─▶ video-voiceover ─▶ video-assemble

流程支持断点续跑:写好 narration.json 后重复同一条命令即可继续。第二阶段会校验 recap_run_manifest.json,拒绝复用来自其他源视频或其他运行参数的旧工作目录;视频理解产物也只在来源一致时复用。

2. 创作职责

这不是单纯的 JSON / 渲染流水线。Agent 是本次内容的创作负责人。先判断本轮的创作控制模式;它与 --edit-mode full|cut|dub 是两个维度:

  • CREATE:从素材创作新成片。比较真正可行的故事/剪辑假设,再选择主线。
  • DIRECTED:用户已经指定结构、镜头、台词或包装方向。把这些决定当作基线落实,不为满足模板而另起方案。
  • REVISION:用户针对已有版本看片修改。最新反馈覆盖旧决定;本轮未点名的故事、镜头、声音和包装默认冻结,不重新发散创作。

REVISION 开始前先明确“本轮修改项”和“冻结项”。表达、节奏、字幕反馈写回 style_card.json,镜头、入出点和声音分工写回 visual_audio_board.json;只有观众承诺、POV、主线或故事 beat 改变时才更新 recap_story_plan.json。删除成片内容时同步删除计划中的旧描述,不能让工作产物继续指导已不存在的镜头。

确定模式后,在进入昂贵的下游处理前完成五次判断:

  1. 导演判断:确定观众承诺、POV、戏剧问题、情绪终点,以及哪些信息要保留到后面揭示。
  2. 故事编辑:CREATE 比较至少两个可行的剪辑假设;DIRECTED / REVISION 继承用户指定或已确认的主线。beat 始终定义为“发生了什么变化”,而不是场景摘要。
  3. 画面剪辑:选择真正值得保留的具体时刻、人物反应、入点与出点。
  4. 声音/旁白:先分配画面、原声、沉默和旁白的任务,再写解说词。
  5. 观众复核:分别检查无旁白、只听声音和第一次观看时的体验,优先修改回报最高的问题。

执行前阅读本技能的 references/creative-editing-playbook.md,并把简洁的创作决定写入:

  • recap_story_plan.json:导演意图、适用时的备选假设、选定主线和基于变化的 beat 图。
  • visual_audio_board.json:每拍的画面任务、表演/反应选择、原声锚点、audio_ownernarration_job
  • style_card.json(有表达要求或表达反馈时):当前声音、口语节奏、字幕阅读姿态与明确禁忌。

这些文件只记录可审计的当前决定,不记录冗长思维过程;它们不会增加服务或渲染依赖。现有工具可以忽略它们,Agent 与建议型解说评审会用它们保持创作一致。建立这条内容基线不需要平台数据。

3. 环境与脚本路径

# ffmpeg: brew install ffmpeg | apt install ffmpeg | choco install ffmpeg
export MIMO_API_KEY=***

同一个 MiMo key 驱动:

  • ASR:mimo-v2.5-asr
  • VLM:mimo-v2.5
  • TTS:mimo-v2.5-tts

TTS 可通过 --tts-provider fish-audio / TTS_PROVIDER=fish-audio 改用 Fish Audio;此时另需 FISH_API_KEY,默认模型为 s2.1-pro-free,默认使用“娱乐扒妹”音色(5653cea4ac83480aaf2bf45406556185),可用 FISH_TTS_REFERENCE_ID 覆盖。ASR/VLM 仍使用 MiMo。

tp-* Token Plan 密钥默认使用中国区集群,可用 MIMO_TOKEN_PLAN_CLUSTER 覆盖。

可选能力:

  • --mimo-video-overview:按场景块补充 MiMo 视频理解。
  • --mimo-qc pre-assemble|post-render|both:在合成前、成片后或两个阶段给出建议型复核。

Read the full file on GitHub · 217 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 217 lines · 128 tokens per session scan A 217913bc6f9e

Subscribe to this mod's changes

video-recap is a skill published in the GitHub repository zenstory-ai/video-recap-skills (505 stars, last pushed today), licensed MIT. It adds 128 tokens to every session and 3,619 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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