Claude Code Agent Development
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用…
Install System Study
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yunshu0909/yunshu_skillshub system-study --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .claude/skills && cp -r skills-src/learning/system-study .claude/skills/system-study && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .claude/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-studyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yunshu0909/yunshu_skillshub system-study --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .agents/skills && cp -r skills-src/learning/system-study .agents/skills/system-study && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .agents/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yunshu0909/yunshu_skillshub system-study --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/learning/system-study .cursor/skills/system-study && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .cursor/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yunshu0909/yunshu_skillshub.git --path learning/system-study--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yunshu0909/yunshu_skillshub system-study --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/learning/system-study .gemini/skills/system-study && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .gemini/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yunshu0909/yunshu_skillshub system-studyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .github/skills && cp -r skills-src/learning/system-study .github/skills/system-study && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .github/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yunshu0909/yunshu_skillshub --skill system-study -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yunshu0909/yunshu_skillshub system-study --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/learning/system-study .opencode/skills/system-study && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "system-study" agent skill from https://github.com/yunshu0909/yunshu_skillshub/tree/master/learning/system-study into .opencode/skills/system-study/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "system-study", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
system-study- GitHub stars
- 767
- Token cost
- ~1.4k tokens
- SKILL.md length
- 422 words
- Files
- 8
- Skills in repo
- 25
- Repo updated
- First seen
- Licence
- MIT
At a glance
系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用…
- Works in 6 steps: ：建工作目录 → ：题目收敛 → ：调研计划 → …
- Tasks that involve Subagents
- SKILL.md covers 工具适配, 5 阶段流程总览, 核心设计原则（5 条） and 5 个 Sub-agent 阵容（A-D 灵活 + E 必选）, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
System Study is an agent skill from yunshu0909/yunshu_skillshub. 系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用 case-radar 给散点）、"把这堆素材整理成 HTML"（用 readable-output 处理已有素材）、文章写作（用 writing-assistant）、整页界面方案（用 page-solution-design）。
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `reference/anti-patterns.md`, `reference/examples-index.md` and `reference/stage-1-topic-narrow.md`).
It sits in Agent Workflows, covering Subagents. The repository describes itself as: 云舒精选的 Claude Code Skills 集合，提升开发和产品管理效率. The licence is MIT.
When your agent uses it
- Tasks that involve Subagents
Example prompts
- “我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透”
- “X 行不行/为什么 Y”
- “X 有哪些好玩案例”
- “/system-study”
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit da0d31f. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
System Study loads about 1.4k tokens when it runs. Until then it costs about 80 tokens; SKILL.md has 422 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from yunshu0909/yunshu_skillshub at commit da0d31f, republished under its MIT licence (© yunshu0909). 422 words, ~1,357 tokens.
Download SKILL.mdSave it as
.claude/skills/system-study/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- system-study
- description
- 系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用 case-radar 给散点）、"把这堆素材整理成 HTML"（用 readable-output 处理已有素材）、文章写作（用 writing-assistant）、整页界面方案（用 page-solution-design）。
- metadata.status
- active
- metadata.status_updated_at
- 2026-10-06
System Study — 系统化学习材料生成
工具适配
文中的 AskUserQuestion、Agent、Read、Write 是能力名称，使用当前平台的等效工具。没有多选界面时，用一条消息列出切片选项，请用户回复编号组合；已明确的信息不重复问。子 agent 按平台并发上限分批执行，先固定全部输入和 prompt，后批不得注入前批的结论。平台没有子 agent 能力时说明限制，再与用户确定逐视角调研方式。
你要学一个新领域。AI 自主调研 + 搭体系 + 产出 HTML 学习材料。
和已有 skill 的本质区别：
- 与结论型调研的区别：结论型调研是"有困惑 → 求结论"；这个是"想学 → 求体系"
- vs case-radar：那个给散点案例集；这个给系统化全貌
- vs readable-output：那个处理已有素材；这个自己挖素材 + 自己建体系（最后可调用它做出稿，但不是核心）
这个 skill 的差异化命门：除了"骨架 + 案例 + 工程化"这些教科书必讲的部分，强制产出"争议焦点 + 盲区清单"两块——这是普通学习材料没有的，是用户研究 → 内容/产品的金矿。
5 阶段流程总览
| 阶段 | 名称 | 介入次数 | 产物 | 详细操作 |
|---|---|---|---|---|
| 1 | 题目收敛 | 1 次（必） | 01-题目确认.md | reference/stage-1-topic-narrow.md |
| 2 | 调研计划 | 1 次（默认） | 02-调研计划.md | reference/stage-2-research-plan.md |
| 3 | Sub-agent 并行调研 | 0 次 | 03-调研笔记/A-E.md | reference/stage-3-subagent-templates.md ⭐ |
| 4 | 体系搭建+大纲确认 | 1 次（默认） | 04-体系大纲.md | reference/stage-4-synthesis.md |
| 5 | HTML 学习材料 | 0 次 | 05-学习材料.html | reference/stage-5-html-spec.md |
默认严格逻辑：阶段 1/2/4 都问用户。但用户可一次性说"全程不打扰、直接出 HTML"，跳过 2、4。阶段 1 永远不能省——题目错了后面全白干。
用户授权"全程不打扰"快速通道
如果用户在阶段 1 / 2 / 任何阶段说出"你直接来吧 / 直接给我结果就行 / 你自己定 / 你判断 / 全程不打扰"——主线程立即切换到快速通道：
- 阶段 1 依然要问（用 AskUserQuestion 弹切片）——题目永远不能 AI 替用户拍
- 阶段 2 仍然写
02-调研计划.md存档，但不再问用户，直接进阶段 3 - 阶段 4 仍然写
04-体系大纲.md存档，但不再问用户，直接进阶段 5 - 在 PLAN.md 标注"用户已授权全程不打扰"——这是审计线索
切换条件：用户的话里明确包含"直接 / 不打扰 / 自己定 / 自己判断 / 你来"等授权词。模糊表达（如"看着办"）不算——继续按默认严格流程问。
核心设计原则（5 条）
这 5 条是从首发实战提炼的、贯穿整个 skill 的设计哲学。所有 stage 都遵循：
- 必经卡点不省——阶段 1 题目收敛永远不能省。其他卡点用户可授权跳过，但题目错了全白干。
- 强制要异见，禁止和稀泥——Agent E 不接受"两边都对"。每个议题必须给 X/10 倾向分。
- 盲区清单独立成块——还没共识的、还在打架的、AI 互相复读的，独立段落，不混在其他内容里。
- 用户研究视角主导——不走"基础→进阶→高阶"教材路线，按"我能拿来做什么"组织。允许带判断、带视角，不需要装客观。
- HTML 独立写，不调 readable-output——学习材料需要侧栏导航 + 章节折叠 + 争议高亮 + 盲区独立区，长文阅读结构不够用。
5 个 Sub-agent 阵容（A-D 灵活 + E 必选）
详细 prompt 模板见 reference/stage-3-subagent-templates.md。
| Agent | 固定职责 | 主题适配方式 |
|---|---|---|
| A 骨架 | 官方文档 + 学派 / 主流方法 | 视主题决定具体源（提示词→Anthropic/OpenAI 文档；记忆系统→各家 memory 文档；MCP→协议文档+实现） |
| B 前沿 | 新形态、新趋势、最新讨论 | 视主题灵活——一句话定义"这领域最新的是什么" |
| C 真物 | 顶级案例 / 真实代码 / 原文拆解 | 必须看原文；案例数量按可信源能找到几个定 |
| D 生态 | 工具景观 / 工程化 / 应用场景 | 直接对接用户的产品决策 |
| E 争议+盲区 | 必选，强制双轨陈述 + 给倾向分 + 盲区清单 | 差异化命门——和市面学习材料的核心区别 |
主线程拿到题目后，根据主题情况微调每个 sub-agent 的具体调研范围（不是改职责类型，是改"查哪些源"），再批量派出。
工作流（主线程要做什么）
Step 0：建工作目录
<主题>学习/ # 默认目录名，可改
├── PLAN.md # 总控
├── 01-题目确认.md
├── 02-调研计划.md
├── 03-调研笔记/
│ ├── A-{骨架切片名}.md
│ ├── B-{前沿切片名}.md
│ ├── C-{真物切片名}.md
│ ├── D-{生态切片名}.md
│ └── E-争议与盲区.md
├── 04-体系大纲.md
└── 05-学习材料.htmlStep 1：题目收敛
- 用
AskUserQuestion（multiSelect: true）给用户 4 个切片选项让她勾 - 切片描述要具体到"覆盖什么"，不要泛泛
- 用户全选也行（这次提示词学习就是 4 个全选）
- 写
01-题目确认.md记录主题 + 学习视角
Step 2：调研计划
- 列出每个 sub-agent 要查的源（官方文档、社区、案例库、争议议题）
- 给用户审一遍，可砍可加
- 用户说"开跑"就进入 Step 3
- 写
02-调研计划.md
Step 3：派 5 个 Sub-agent 并行
- 每个 sub-agent 用当前平台独立的子 agent 调用；下文
Agent为能力示意 - 启动前固定全部 5 个 prompt，按平台可用并发上限派出；需要分批时，不将前批结果注入后批
- prompt 模板见 reference/stage-3-subagent-templates.md
- 必须包含的硬约束（见 anti-patterns.md）：
- 分段写入文件（每完成 1-2 节就 Write 一次）
- 反 AI 文废话清单
- 来源可追溯
- 争议必须双轨 + 给倾向
Show full SKILL.md (159 more words)Show less
Step 4：合成 + 大纲确认
- 读全部 5 份调研笔记
- 设计 8 篇章节结构（导读 / 骨架 / 实战 / 进阶 / 案例 / 工程化 / 争议 / 盲区 / 附录）
- 写
04-体系大纲.md - 给用户过一遍坐标系
Step 5：HTML 产出
- 按 stage-5-html-spec.md 的设计 token 和组件规范
- 单文件 HTML，所有 CSS 内嵌
- 必须包含：左侧固定导航 / 4 种 callout / 案例 details 折叠 / 争议带倾向分 / 盲区清单
- 一次写完，不要分多次 Write（防止截断时被中间状态打断）
关键硬约束（一定要看 anti-patterns.md）
- Sub-agent 必须分段写入文件——不能等最后一次性写。socket 崩溃会丢全部内容。
- Agent E 强制双轨 + 给倾向分——"两边都对"不接受。
- 案例类 Agent 强制 3+ 个原文片段 + 可信度评级——AI 总结的二手案例不接受。
- AI 文废话黑名单——明显套话密度高的中文博客跳过。
- 主线程做合成，不下放给 sub-agent——sub-agent 只产物料。
- PLAN.md 主控——每次状态变化更新进度表。
灵活参数
| 参数 | 默认 | 可调 |
|---|---|---|
| 切片数量 | 4（A-D）+ 1（E）= 5 | 3-6（E 必含） |
| 介入级别 | 阶段 1/2/4 各一次 | 用户可授权全跳过 2 和 4 |
| 产物目录名 | <主题>学习/ | 用户可改 |
| HTML 风格 | 浅色暖白 | 可扩深色 / 暗紫调（暂未实现） |
| Sub-agent 派出方式 | 固定 5 个独立 prompt，按平台并发上限执行 | 不用前批结论改写后批输入 |
不适用于（边界划清）
- "X 行不行 / 为什么 Y / 评估 X 可行性" → 当前可用的调研工具
- "X 领域有哪些好玩案例 / 看看大家在玩什么" →
case-radar（散点 vs 体系） - "把这堆素材整理成 HTML" →
readable-output（处理已有素材 vs 自己挖素材） - "写文章 / 出初稿" →
writing-assistant - "做设计稿 / UI 原型" →
page-solution-design（整页方案）；具体样式修改按已有界面直接调整 - "PRD / 需求文档" →
prd-test-writer
参考实例
首发实战：项目根目录 提示词学习/（2026-05-14 跑通的真实案例）
- 主题：提示词学习（4 切片全选）
- 实际耗时：~30 分钟
- 产物：5 份调研笔记 ~180KB → HTML 学习材料 120KB（1635 行）
- 卡点教训：见 anti-patterns.md 的"Agent B socket 崩溃"案例
后续每跑一个新主题，建议在 examples-index.md 里记一笔，作为后续主题的参考。
© yunshu0909, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files in learning/system-study of yunshu0909/yunshu_skillshub.
- SKILL.md
- reference/anti-patterns.md
- reference/examples-index.md
- reference/stage-1-topic-narrow.md
- reference/stage-2-research-plan.md
- reference/stage-3-subagent-templates.md
- reference/stage-4-synthesis.md
- reference/stage-5-html-spec.md
Open the folder on GitHubat commit da0d31f
Compare with similar skills
System Study next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| System Study this skillyunshu0909/yunshu_skillshub | 767 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Claude Code Agent Developmentanthropics/claude-plugins-official | 38k | 7 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Subagent Driven DevelopmentAsvarox/allkaraoke | 261 | 37 repos | ~1.2k | Automated safety check: Pass | None | |
| Dispatching Parallel Agentsultralisp/ultralisp | 258 | 40 repos | ~1.5k | Automated safety check: Pass | None | |
| Paseo Advisor Second Opiniongetpaseo/paseo | 20k | 1 repos | ~756 | Automated safety check: Pass | Custom licence | |
| Task Observerrebelytics/one-skill-to-rule-them-all | 3.2k | 1 repos | ~12k | Automated safety check: Pass | CC-BY-4.0 |
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- Official
Subagent Driven Development
Asvarox/allkaraoke
A skill your agent uses when executing implementation plans with independent tasks in the current session
Dispatching Parallel Agents
ultralisp/ultralisp
A skill your agent uses when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
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Launches one separate agent through Paseo to give a second opinion on the current task, with a self-contained briefing and no permission to edit files.
Task Observer
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O2 Review Loop
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Splits a change into planner, coder and independent reviewer roles: you confirm a spec, a subagent implements it, and a separate reviewer checks each round's local WIP commit.
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Questions about System Study
What does System Study do?
系统化学习材料生成器。给一个新领域/技术/概念，AI 自主调研、搭体系、产出 HTML 学习材料（含骨架/案例/工程化/争议+盲区）。当用户说"我要学 X / 帮我系统拆解 X / 我想吃透 X 这个领域 / 给我整理 X 的全貌 / 深度调研 X 给我系统讲讲 / 把 X 搞透"时触发。不适用于"X 行不行/为什么 Y"（使用可用的调研工具直接研究）、"X 有哪些好玩案例"（用…. System Study is an agent skill from yunshu0909/yunshu_skillshub.
When should I use System Study?
System Study fits situations like: tasks that involve Subagents.
How do I install System Study in Claude Code?
Run `npx skills add yunshu0909/yunshu_skillshub --skill system-study -a claude-code`. Or copy the skill folder (learning/system-study in yunshu0909/yunshu_skillshub) into .claude/skills/system-study in your project. Claude Code loads it when a task matches its description.
How do I install System Study in Codex?
Run `npx skills add yunshu0909/yunshu_skillshub --skill system-study -a codex`. Or copy the skill folder (learning/system-study in yunshu0909/yunshu_skillshub) into .agents/skills/system-study in your project. Codex loads it when a task matches its description.
Can I use System Study in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yunshu0909/yunshu_skillshub --skill system-study -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/system-study, .gemini/skills/system-study, .github/skills/system-study and .opencode/skills/system-study in your project.
What does System Study need to run?
SKILL.md names no scripts, command-line tools or credentials: System Study is instructions for the agent only.
Does System Study access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is System Study safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does System Study use?
System Study is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does System Study use?
About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to System Study?
Skills that share tags, products or a category with System Study: Claude Code Agent Development (anthropics/claude-plugins-official, 38k stars), Subagent Driven Development (Asvarox/allkaraoke, 261 stars), Dispatching Parallel Agents (ultralisp/ultralisp, 258 stars) and Paseo Advisor Second Opinion (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains System Study?
yunshu0909 (a GitHub user) maintains it in yunshu0909/yunshu_skillshub, which has 767 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 6, 2026.
Source: yunshu0909/yunshu_skillshub on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.