system-study

system-study is a skill for Claude Code, Codex from yunshu0909/yunshu_skillshub. It costs 186 tokens per session (3,108 once invoked), scanned A, original, MIT.

A structured learning-material generator for a new field or technology that researches the topic, builds an organised overview, and produces an HTML study guide.

In plain words
What is it for?
Use it when you want to systematically learn a subject, with its basic structure, examples, implementation concerns, debates, blind spots, and a finished HTML reference.
Why use it?
It helps someone move from scattered information to a complete learning path. The material also includes practical engineering concerns, disagreements, and commonly overlooked gaps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; names the AskUserQuestion tool.

Good fit Use it when you want to systematically learn a subject, with its basic structure, examples, implementation concerns, debates, blind spots, and a finished HTML reference.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yunshu0909/yunshu_skillshub/system-study
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 yunshu0909/yunshu_skillshub --skill system-study
Clone the repo
git clone --depth 1 https://github.com/yunshu0909/yunshu_skillshub

Made for: Claude Code, 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 system-study

README.md
[![agentmods](https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/system-study/github.svg)](https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/system-study)
Your own site
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/system-study"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/system-study/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 system-study

Your own site · 80×15
<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/system-study"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/system-study.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 186 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,108 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 $0.00186 $0.03108
Opus 5.5 $0.00074 $0.01243
Sonnet 5.5 $0.00037 $0.00622
Haiku 4.5 $0.00019 $0.00311

Measured 1mo ago against content hash f505b4fdf8a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

system-study 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 1mo 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.

learning/system-study/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

  1. 阶段 1 依然要问(用 AskUserQuestion 弹切片)——题目永远不能 AI 替用户拍
  2. 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
  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
  4. 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:

  1. 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。
  2. 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。
  3. 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。
  4. 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。
  5. 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。

Read the full file on GitHub · 177 lines

Files

What ships with it

7 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. 1mo ago Changed · +8 lines · +8 tokens per session f505b4fdf8a5
  2. 2mo ago First seen · 169 lines · 178 tokens per session scan A 466b647e01f2

Subscribe to this mod's changes

system-study is a skill published in the GitHub repository yunshu0909/yunshu_skillshub (789 stars, last pushed 26d ago), licensed MIT. It adds 186 tokens to every session and 3,108 once invoked, about $0.0007 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 2026-08-30.

Related

system-study compared with skills from other repositories

system-study next to 6 skills from other repositories
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system-studyyunshu0909/yunshu_skillshubSkill78926d agoMITA186Claude Code, Codex
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