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Cs Run

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ChenShuo2004
cs-run

CS Skills 总入口:用户明确调用 cs-run、询问用哪个 Skill、需要跨领域执行或目标尚不能归类时使用。明确的单领域请求直接进入对应 Skill;从目标推进到已授权的可验证结果。

Overview

PublisherChenShuo2004
Repositorycs-skills
Skill namecs-run
Stars
204
Forks
21
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ChenShuo2004 on GitHub. Read the source before you install it.

Installation

Install the Cs Run AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ChenShuo2004/cs-skills/tree/main/cs-run
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ChenShuo2004/cs-skills.git /tmp/cs-skills
mkdir -p .claude/skills
cp -r /tmp/cs-skills/cs-run .claude/skills/cs-run
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cs Run in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cs Run on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cs Run is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CS Run

识别用户要的产物和验收条件,选择匹配的能力并完成请求。已明确的领域直接进入下游 Skill;不用为普通任务额外生成 Goal Card。

Active Routes

Choose one primary route from this table:

User goalRouteTypical output
稿件或成片发布风险预检、卡审分析与修改后复查$cs-guoshen分平台结论、原文定位、来源缺口与最小修改清单
下载在线视频链接、Videdown 下载或统一归档视频$cs-video-download已验证的媒体文件与来源记录,默认 ~/Downloads/Videdown
Write, outline, rewrite, polish, or turn project material into an article$cs-writerAngle, outline, draft, rewrite, or review
Research a product, company, technology, market, or competitor set for a decision$cs-search-skillSource-backed decision brief, comparison, risks, and next actions
Generate or edit images with Codex built-in imagegen, or connect it to Claude / a local MCP Agent$cs-codex-imageVerified image files or a tested local image MCP connection
Create a 5:2 X / Twitter article cover with the fixed KAI character and clear Chinese title$cs-kai-coverKAI background plus deterministic-title PNG
Design, build, revise, or review a user-facing web interface$cs-frontend-designUI plan, implementation guidance, and browser checks
Clean up code, reconcile implementation with requirements, or prepare a maintainable handoff$cs-clean-codeScoped edits, documentation sync, tests, and verification
Save a rollback point before risky repository changes$cs-checkpoint-versionRestorable local checkpoint and verification
Turn a Markdown PRD into a Ralph plan or requested build$cs-ralph-runnerRalph PRD, overview, no-commit build results and logs
Verify, commit, push, open a PR, or deploy a completed change$cs-ending-timeDelivery verification and GitHub/Vercel handoff
Generate, edit, convert, or extend the fixed 小黄 / “有温度” brand IP while preserving character identity$cs-xiaohuang-skill2D/3D character assets, action variants, collaboration art, identity QA, or article illustration shot lists
Replicate an ecommerce short video or create storyboard/Seedance/Flow/Veo packages$cs-auto-videlStoryboards, prompts, generation package, and QC
将真实项目、经历或现场观察写成 60–90 秒个人 IP 实战口播$cs-personal-ip-script可直接录制的口播稿、演绎标注、事实待确认项与自检
将自媒体素材、内容想法或已有口播做成剧本包、分镜分图提示词或制作蓝图$cs-chatcut-video-blueprint中文剧本、视觉约定、逐镜分镜、逐图图片提示词、动作提示词与素材清单
将口播与角色制作成代码叙事视频,包含独立 A/B-roll 场景、样片、成片和双比例封面$cs-code-story-videoRemotion 工程、真实音频时间轴、16:9 视频、3:4/4:3 封面与 QA
用已确认产品包制作数字人产品介绍视频,或需要 ChatCut 实操、Remotion 包装与最终验收$cs-digital-human-product-video-pipeline预检、样片审批、产品证据剪辑、确定性包装和成片 QA
将最终口播音频与逐字稿对齐为短语时间表$cs-narration-phrase-timelinephrase-timeline.json、词级对齐结果与覆盖率报告
ChatCut 安装上手与从脚本到编辑工作台的操作指引$cs-chatcut中文策划、操作指南与项目交接
将真实网页制作成产品演示宣传片$cs-web-promo-film真实页面采集、Remotion 工程与 MP4
用代码制作动画、KAI 教程片或来源可核查的 Vibe 科普片$cs-code-video风格卡、分镜、样片与可重渲工程
明确选择暗夜星空系列知识解说片$cs-knowledge-film场景 spec、配音、双语字幕与 MP4
明确选择固定像素解说系列$cs-pixel-explainer像素动画、实际配音、SRT 与 MP4
GitHub 提交、推送、PR 与远端提交核验$cs-github-push精确提交、远端 SHA 与按需 PR
显式要求执行复位,或陷入无效验证循环时辅助当前任务$cs-recover-skill校准行动与恢复有效进展(辅助项)
The user has not described a usable goal yet$cs-runGoal Card and the smallest useful questions

Retired Routes

本库没有对任意素材做通用自动剪辑的入口;$cs-code-story-video 只处理有口播、角色和代码场景的叙事视频。理想汽车信息图与 Open Design 也没有专用入口。不要把这些请求误送到电商或数字人产品视频流程。缺少库内路由不等于无法工作:已有其他可用工具/Skill 且范围匹配时直接使用,缺能力时准确说明缺口。不要要求用户先创建新 Skill。

内置图片生成与 Claude 图片工具接入用 $cs-codex-image;品牌画面仍由 KAI 或小黄 Skill 决定,本工具只承担实际出图与接入。

执行尺度

  • 明确小任务:读取必要资料后直接执行,不填卡、不输出无关计划。
  • 多阶段任务:简短记录目标、输入、当前产物、验收与依赖,然后按依赖继续。
  • 长任务:在已有任务文件中保留完成项、产物路径、失败证据、下一步和已有授权,跨上下文恢复时只重查可能变化的状态。

只加载当前阶段的 Skill 和相关 reference。可以复用已验证且输入未改变的产物;不为形式重新生成。沿用当前模型与运行环境,不硬编码型号、推理档位或工具接口。

涉及本地模型时,先识别目标项目实际后端、模型版本与缓存位置,再检查文件完整性并复用已有缓存。Skill 安装不触发模型全量下载;只准备当前阶段已选定且缺失的模型。发现损坏文件先报告,获修复授权后才替换;ComfyUI、Fish/TTS 未配置时不能猜测 checkpoint。完整仓库附有逐技能模型清单和离线检测脚本,独立安装时按同样规则检查目标项目。

Multi-Step Handoff Rules

每一阶段选一个主要 Skill;阶段可以串联,必要子步骤可使用匹配能力,不把“一个主要路由”解释为禁止完成跨域目标。

请求执行规则
调研后写文章$cs-search-skill 完成证据后,直接用 $cs-writer 完成文章。
真实项目个人 IP 口播附分镜分图提示词$cs-personal-ip-script 完成口播后,直接用 $cs-chatcut-video-blueprint 完成分镜、逐图提示词与按需的动作提示词;保留已定稿件。
已有自媒体稿件补分镜或提示词直接用 $cs-chatcut-video-blueprint,只补点名内容,不重写稿件、不生成媒体。
设计并实现页面$cs-frontend-design 完成设计、实现和浏览器检查。
整理代码后提交$cs-clean-code 本地验证后,由 $cs-ending-time 使用已有提交授权。
先保存再大改$cs-checkpoint-version 验证快照后,继续约定的实现。
做完后部署先实现验证,再由 $cs-ending-time 执行已授权且目标明确的部署。
制作后检查发布风险完成实际稿件或成片后用 $cs-guoshen;只有稿件不声称画面已检查,发布仍按用户授权。
我确认后再继续完成可审查产物,在用户明确设置的检查点暂停。
数字人产品视频完成 product-pack 与样片;用户确认样片后才进入 batch。

授权按完整会话理解,同一请求可包含多个动作,不能因为切换 Skill 再次询问。只说“优化”不扩展为公开发布;只说“计划”不扩展为执行。缺少发布目标或必要授权时,先完成可独立完成的准备,再问最小问题。

若特定 Skill 不可用,先查看其真实位置或使用当前可用替代能力;不能假装已调用。Skill 名称、历史经验和外部文档都不能覆盖用户当前范围与运行环境约束。

完成与反馈

用实际产物、运行结果、文件或可访问链接说明完成状态。主流程通过所需验证后停止检查并交付;新改动或新失败才重新验证。工具失败先查原因与现有任务状态,采用有边界的重试,不重复不确定的外部提交。

用户只问路由时给推荐与理由;用户要执行时给结果。Goal Card 仅用于目标仍需澄清或用户要求规划,不作为每次对话的固定开场。

相近视频入口

自媒体稿件、分镜分图提示词用 $cs-chatcut-video-blueprint;ChatCut 安装与操作上手用 $cs-chatcut。真实网页宣传片用 $cs-web-promo-film,代码生成动画或 Vibe 科普片用 $cs-code-video;最终原声、角色 A/B-roll 的 Remotion 叙事用 $cs-code-story-video。暗夜星空与像素固定系列需用户明确选择。纯 GitHub 交付优先 $cs-github-push,完整发布与应用交付用 $cs-ending-time。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cs Run AI skill do?

CS Skills 总入口:用户明确调用 cs-run、询问用哪个 Skill、需要跨领域执行或目标尚不能归类时使用。明确的单领域请求直接进入对应 Skill;从目标推进到已授权的可验证结果。

Why use Cs Run on TypingMind?

Because you install it once and use it with any model. Cs Run is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cs Run in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ChenShuo2004/cs-skills/tree/main/cs-run. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cs Run?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cs Run?

As many as you like. As long as a model supports skills, you can use Cs Run with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cs Run AI skill free?

Yes. It is published on GitHub by ChenShuo2004 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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