cs-chatcut-video-blueprint

cs-chatcut-video-blueprint is a skill for Codex from ChenShuo2004/cs-skills. It costs 74 tokens per session (1,323 once invoked), scanned A, original, MIT.

A writing and planning workflow for turning Chinese media ideas, source material, or existing narration into a script and video blueprint. A blueprint is a written production plan with shots, image prompts, and optional movement prompts, not a finished video.

In plain words
What is it for?
Use it for topic selection, narration writing, shot lists, per-image prompts, or a complete pre-production package for tutorials, project reviews, opinion videos, and short scenes. It stops at the text and planning stage rather than operating the project or exporting media.
Why use it?
It helps turn loose ideas into a recordable script and a clear handoff for filming or editing without inventing facts, personal experiences, or exact audio timings. It also lets you add only the missing planning pieces to an existing script.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: $skill-name invocation.

Good fit Use it for topic selection, narration writing, shot lists, per-image prompts, or a complete pre-production package for tutorials, project reviews, opinion videos, and short scenes. It stops at the text and planning stage rather than operating the project or exporting media.

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Install with agentmods
npx agentmods add skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint
Install

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.

Any agent
npx skills add ChenShuo2004/cs-skills --skill cs-chatcut-video-blueprint
Clone the repo
git clone --depth 1 https://github.com/ChenShuo2004/cs-skills

Made for: Codex.

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 cs-chatcut-video-blueprint

README.md
[![agentmods](https://agentmods.dev/badge/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint/github.svg)](https://agentmods.dev/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint)
Your own site
<a href="https://agentmods.dev/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint"><img src="https://agentmods.dev/badge/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint/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 cs-chatcut-video-blueprint

Your own site · 80×15
<a href="https://agentmods.dev/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint"><img src="https://agentmods.dev/badge/skills/chenshuo2004/cs-skills/cs-chatcut-video-blueprint.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,323 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.
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 $0.00074 $0.01323
Opus 5.5 $0.00030 $0.00529
Sonnet 5.5 $0.00015 $0.00265
Haiku 4.5 $0.00007 $0.00132

Measured 18d ago against content hash dad48e9fefc8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cs-chatcut-video-blueprint 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 18d 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.

cs-chatcut-video-blueprint/SKILL.md · 55 lines

What it actually says

CS 自媒体剧本与制作蓝图

把真实素材变成可录制、可拍摄、可逐图准备的视频文本包,适用于观点口播、项目复盘、教程演示和情景短剧。可交接到 ChatCut 或其他匹配工具;名称保留原调用方式,文本交付不依赖 ChatCut。默认简体中文。

按请求决定交付深度

  • 只选题:去重、比较受众相关性、观点张力、事实支撑和制作可行性,推荐一个主题。只有比较确有帮助时才打分。
  • 只写口播:直接给可复制的完整稿件,不展开分镜。
  • 要自媒体剧本包、剧本附分镜分图提示词或完整蓝图:连续完成正文、视觉约定、逐镜分镜、逐图图片提示词、按需的动作提示词与素材缺口;不要求用户额外说“端到端”。
  • 已有稿件只补分镜或提示词:保留原稿、已定风格和台词,只交付点名范围;不重开选题、不重写正文。
  • 用户要求“先给我选题”“稿子确认后再继续”时,按其明确阶段停下。已有确认继续有效;需要改变已锁定事实、立场或稿件时才说明变更。

从素材推断平台、时长、受众与语气,并简短标注会影响结果的假设。事实来源、说话人真实经历不能猜;缺少关键依据时给出能完成的稿件部分和最小缺口。不要把完整 brief 当作问卷。

自媒体故事开发

需要从素材写剧本、修正中段推进或去模板感时,读取 自媒体剧本方法。先确定内容承诺和可成立的结尾,再按内容形式检查因果或论证;不为填表硬加对手、倒计时、反转或金句。

真实项目的个人 IP 口播可先用 $cs-personal-ip-script 成稿,再在同一请求内接着完成这里的分镜与提示词。已有正文直接复用;只要口播时不增加文本制作包。

口播质量

  • 每条只针对一个具体人群、场景和问题。开头用可识别的事实、损失、动作或矛盾,让观众立刻知道与自己的关系。
  • 每段推进新事实、例子、解释或行动;不重复换说法。结构服从内容,不强塞固定的 Hook、冲突、结论模板。
  • 产品能力、数字与经历回链到素材;用户观点与外部事实分开。未证实的卖点不能写成肯定断言。
  • 纯口播与停顿、重音等表达标注分开,避免被配音读进台词。只在用户需要时提供多个 Hook 或标注稿。
  • 以可朗读字数和明确语速假设估算时长,标为“预计”。最终音频才决定真实时码;不能声称仅凭字数通过了实听或精确时长验收。
  • CTA 最多一个动作;内容不需要引导时可以没有 CTA。明确无 BGM 时,不增加音乐设计。

制作蓝图

需要分镜、分图或生成提示词时读取 分镜与逐图提示词,按镜号关联台词、图片与动作;每条生成提示词完整可复制,不以“同上”省略。需要保存完整剧本包时使用 文本包模板。

完整制作蓝图另读 蓝图格式。每个素材和 Motion Graphics 都要对应具体口播与观看任务;透明叠加、全屏不透明画面要区分,保护人物、产品 UI 与字幕。实拍、录屏和证据截图写获取指令,不能用生成图伪造真实项目证据。

计划时码不能冒充最终音频对齐。已有最终音频且用户需要字幕或动画真实时间时,可交接给 $cs-narration-phrase-timeline。

数字人产品视频的交接读取 产品包摘要,保留事实、禁用断言、证据编号、规格、声音来源和 sample-then-batch 规则。只有满足产品包范围的制作才交给 $cs-digital-human-product-video-pipeline;普通 ChatCut 剪辑不误送到这个专用管线。

执行边界与完成

  • 不创建、选择或修改 ChatCut 项目。
  • 不上传、导入、导出、渲染或把素材放入时间线。
  • 不调用 ChatCut MCP、不编写 Motion Graphics JSX、不虚构 asset ID。
  • 可以在用户指定的本地目录保存脚本、蓝图和产品包草稿。用户要求制作视频时先交付本阶段产物,再使用实际可用且匹配的制作工具。
  • 交付前核对事实来源、口播推进、镜号与图号引用、关键内容的画面/声音承载、跨镜连续性和计划时长覆盖。提示词条目不代表已生成媒体;静态检查不代表画面质量或传播效果。
  • 先给用户所需成品,仅附影响继续制作的待确认项。
Files

What ships with it

6 files 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.

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. 18d ago First seen · 55 lines · 74 tokens per session scan A dad48e9fefc8

Subscribe to this mod's changes

cs-chatcut-video-blueprint is a skill published in the GitHub repository ChenShuo2004/cs-skills (204 stars, last pushed 18d ago), licensed MIT. It adds 74 tokens to every session and 1,323 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-07.

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