chengfeng-videocut-skills is a Codex plugin that coordinates Chinese voiceover video editing through the chengfeng-videocut runtime, whose command-line tools and APIs perform the actual processing. It is for agents that need to edit and export narrated videos, while its catalogue skills handle decisions and workflow coordination around that runtime.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Agentchengfeng/chengfeng-videocut-skills --skill chengfeng-exportgit clone --depth 1 https://github.com/Agentchengfeng/chengfeng-videocut-skillsWrote 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.
[](https://agentmods.dev/skills/agentchengfeng/chengfeng-videocut-skills/chengfeng-export)<a href="https://agentmods.dev/skills/agentchengfeng/chengfeng-videocut-skills/chengfeng-export"><img src="https://agentmods.dev/badge/skills/agentchengfeng/chengfeng-videocut-skills/chengfeng-export/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.
<a href="https://agentmods.dev/skills/agentchengfeng/chengfeng-videocut-skills/chengfeng-export"><img src="https://agentmods.dev/badge/skills/agentchengfeng/chengfeng-videocut-skills/chengfeng-export.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.02654 |
| Opus 5 | $0.00041 | $0.01327 |
| Sonnet 5 | $0.00016 | $0.00531 |
| Haiku 4.5 | $0.00008 | $0.00265 |
Grade A, and why
chengfeng-export 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 11d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
导出（成片）
这是链条最后一段，也是整个产品里唯一一个真正画出像素的地方。
在它之前全部是标注：账本记「播哪些词」，字幕记「屏上写什么」，画面记「盖什么层」， 预览把这三样实时拼给人看，不落盘。导出把它们烧成一个文件。
需要 edit-list.json（必须）、subtitles.json、visuals.json + modules/
产出 成片.mp4
前提工具：机器上有 Google Chrome（用来把字幕和动画画成图）。桌面安装来源的
FFmpeg / FFprobe 已随 App 进入 Product 受管目录；纯 CLI 安装仍要求系统
ffmpeg ≥ 6。缺 Chrome 会明确报错，不要试图绕过——没有它就没有字幕层和动画层。
先读取并执行 业务 Skill 的阶段合同 里的「结论等级」一节。导出不进剪辑状态机：它不改任何项目文件、不做 CAS 写入、 不推进 stage，产出是一个新文件，重跑一次就覆盖。所以它不需要确认卡。
0. 就绪
先执行 检查更新 的「就绪检查」——skills 是否
最新、Runtime 是否配套；插件根也在那里定位（本文命令里的 <插件根> 都代入
那个字面路径）。只有「就绪」才继续；「需新会话」或「停」按它的处置执行
（含「禁止自制替代界面」禁令），业务 Skill 不自带环境逻辑。
若就绪结果为 runtime.kind=desktop-managed，直接复用桌面 App 已安装的稳定 CLI、
媒体工具与同一 launchd/windows-task 服务；不要解析 Electron 路径、另装
FFmpeg/Bun 或起第二个 Runtime。
命令
node "<插件根>/scripts/ensure-running.cjs" --json
node "<插件根>/scripts/videocut-cli.cjs" export <project> --dry-run --json # 先看计划，不编码
node "<插件根>/scripts/videocut-cli.cjs" export <project> --json # 出成片（默认 2 倍、源帧率）
node "<插件根>/scripts/videocut-cli.cjs" export <project> --out /path/成片.mp4 --json
node "<插件根>/scripts/videocut-cli.cjs" export <project> --scale 1 --json # 只要源尺寸
node "<插件根>/scripts/videocut-cli.cjs" export <project> --keep-work --json # 留下中间片和逐帧 PNG，供排查
ensure-running 身份不匹配、端口冲突或服务不健康时立即停止；不允许用 foreground
临时顶替后继续导出。
两步，别只跑第二步
① --dry-run 先报计划 片长、帧数、字幕屏数、画面层数、推近段数、输出尺寸
念给用户听。数字不对就是上游不对，编码十分钟不会修好它
② 真跑 assemble → overlay → compose → verify 四段进度
--dry-run 里的 warnings 必须原样转述。它只报一类事：某些字幕屏或画面层的词
已经被剪掉了，所以它们不会出现在成片里。这是上游要决定的事，不是导出该替人吞掉的。
清晰度：源片是天花板，先看源再谈放大
导出前看一眼源分辨率（--dry-run 的 source 字段就有）：
源宽 ≥2560（Retina 原生录屏） → --scale 1，输出就是原生像素，这是最好的情况
源宽 <1920（如 960×720） → 先停一下：问用户有没有同一次录制的高清导出。
录屏工具常常能把同一次录制重新导出成 3 倍分辨率，
换源比任何后期都管用（见下节）。确实没有 → --scale 2
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 173 lines · 82 tokens per session scan A 7d08a11ad76f
chengfeng-export is a skill published in the GitHub repository Agentchengfeng/chengfeng-videocut-skills (2,986 stars, last pushed 3d ago), licensed Apache-2.0. It adds 82 tokens to every session and 2,654 once invoked, about $0.0004 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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