Codebase Management
giancarloerra/SocratiCode
Set up, index, and manage SocratiCode codebase indexing. An agent skill from giancarloerra/SocratiCode.
AI Engineering from Scratch 的阶段测验。用于“给我测验一下”、“测试阶段”、“检查我的理解”、“我掌握第 3 阶段了吗”，也支持 "quiz me", "test phase", "check my understanding", "do I know phase 3" 或 /check-understanding <phase。
Install Check Understanding
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh check-understanding --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/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/check-understanding .claude/skills/check-understanding && 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 "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .claude/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understandingType 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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh check-understanding --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/check-understanding .agents/skills/check-understanding && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .agents/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh check-understanding --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/check-understanding .cursor/skills/check-understanding && 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 "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .cursor/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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/fancyboi999/ai-engineering-from-scratch-zh.git --path skills/check-understanding--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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh check-understanding --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/check-understanding .gemini/skills/check-understanding && 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 "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .gemini/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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 fancyboi999/ai-engineering-from-scratch-zh check-understandingInstalls 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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/check-understanding .github/skills/check-understanding && 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 "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .github/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh check-understanding --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/check-understanding .opencode/skills/check-understanding && 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 "check-understanding" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/skills/check-understanding into .opencode/skills/check-understanding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "check-understanding", 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
check-understanding- GitHub stars
- 1.2k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 317 words
- Files
- 1
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- MIT
At a glance
AI Engineering from Scratch 的阶段测验。用于“给我测验一下”、“测试阶段”、“检查我的理解”、“我掌握第 3 阶段了吗”，也支持 "quiz me", "test phase", "check my understanding", "do I know phase 3" 或 /check-understanding <phase。
- Works in 3 steps: 重做本测验 —— 从同一阶段生成一组新的 8 道题 → 测试另一阶段 —— 选择其他阶段测试 → 解释一个主题 —— 询问任意错题涉及的概念
- AI & LLM Engineering work in your project
- SKILL.md covers 触发方式, 输入, 阶段映射 and 流程, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Check Understanding is an agent skill from fancyboi999/ai-engineering-from-scratch-zh. AI Engineering from Scratch 的阶段测验。用于“给我测验一下”、“测试阶段”、“检查我的理解”、“我掌握第 3 阶段了吗”，也支持 "quiz me", "test phase", "check my understanding", "do I know phase 3" 或 /check-understanding <phase。
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering. It works with Model Context Protocol. The repository describes itself as: Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南. The licence is MIT.
When your agent uses it
- AI & LLM Engineering work in your project
Example prompts
- “给我测验一下”
- “检查我的理解”
- “我掌握第 3 阶段了吗”
- “/check-understanding”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- 重做本测验 —— 从同一阶段生成一组新的 8 道题
- 测试另一阶段 —— 选择其他阶段测试
- 解释一个主题 —— 询问任意错题涉及的概念
What it can do on your machine
Read from SKILL.md and the folder at commit 94b9888. 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
Check Understanding loads about 1.1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 317 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 fancyboi999/ai-engineering-from-scratch-zh at commit 94b9888, republished under its MIT licence (© fancyboi999). 317 words, ~1,053 tokens.
Download SKILL.mdSave it as
.claude/skills/check-understanding/SKILL.md (or your agent's skills folder).- name
- check-understanding
- description
- AI Engineering from Scratch 的阶段测验。用于“给我测验一下”、“测试阶段”、“检查我的理解”、“我掌握第 3 阶段了吗”，也支持 "quiz me", "test phase", "check my understanding", "do I know phase 3" 或 `/check-understanding <phase>`。
- version
- 1.0.0
检查理解程度
测试学习者对 AI Engineering from Scratch 已完成阶段的掌握情况。
触发方式
当用户说出类似下面的话时启用此 skill：
/check-understanding 3或/check-understanding deep-learning- “测验一下我对第 2 阶段的掌握情况”
- “测试第 1 阶段”
- “检查我对 transformer 的理解”
- “我掌握第 3 阶段了吗”
- “我准备好进入下一阶段了吗”
输入
接受阶段编号（0-19）或阶段名称作为参数。如果没有参数，列出全部 20 个阶段，并询问用户希望测试哪一阶段。
阶段映射
将参数映射到 phases/ 下正确的阶段目录：
| 输入 | 目录 | 阶段名称 |
|---|---|---|
| 0, setup, tooling | 00-setup-and-tooling | 环境设置与工具 |
| 1, math, math-foundations | 01-math-foundations | 数学基础 |
| 2, ml, ml-fundamentals | 02-ml-fundamentals | 机器学习基础 |
| 3, deep-learning, dl | 03-deep-learning-core | 深度学习核心 |
| 4, cv, computer-vision, vision | 04-computer-vision | 计算机视觉 |
| 5, nlp | 05-nlp-foundations-to-advanced | NLP：从基础到进阶 |
| 6, speech, audio | 06-speech-and-audio | 语音与音频 |
| 7, transformers | 07-transformers-deep-dive | Transformer 深入剖析 |
| 8, generative, gen-ai, genai | 08-generative-ai | 生成式 AI |
| 9, rl, reinforcement-learning | 09-reinforcement-learning | 强化学习 |
| 10, llms, llm, llms-from-scratch | 10-llms-from-scratch | 从零构建 LLM |
| 11, llm-engineering, llm-eng | 11-llm-engineering | LLM 工程 |
| 12, multimodal | 12-multimodal-ai | 多模态 AI |
| 13, tools, protocols, mcp | 13-tools-and-protocols | 工具与协议 |
| 14, agents, agent-engineering | 14-agent-engineering | Agent 工程 |
| 15, autonomous | 15-autonomous-systems | 自主系统 |
| 16, multi-agent, swarms | 16-multi-agent-and-swarms | 多 Agent 与群体 |
| 17, infrastructure, production, infra | 17-infrastructure-and-production | 基础设施与生产环境 |
| 18, ethics, safety, alignment | 18-ethics-safety-alignment | 伦理、安全与对齐 |
| 19, capstone, projects | 19-capstone-projects | 综合项目 |
流程
第 1 步：解析阶段
解析参数。若为数字，验证它是否在 0 到 19（含）之间。数字超出范围时，告诉用户：阶段 [N] 不存在。有效阶段为 0-19。然后展示完整列表供其选择。若为名称或关键词，在上方阶段映射中查找。关键词不匹配任何条目时，告诉用户：未知阶段“[keyword]”。请从下面列表中选择：，并展示全部 20 个阶段。未提供参数时，要求用户从完整列表中选择。
第 2 步：读取阶段内容
如果仓库已克隆（当前目录或其父目录存在 phases/），找出 phases/<phase-dir>/ 下全部课程目录并读取每课的 docs/zh.md。如果未克隆，从 README 的 Contents 部分获取该阶段课程列表（获取 https://raw.githubusercontent.com/fancyboi999/ai-engineering-from-scratch-zh/main/README.md），再从同一 raw base URL 获取每课的 docs/zh.md。这些文档就是出题依据。
读取足够多的课程文档，以覆盖该阶段的完整广度。阶段课程很多（15+）时，优先读取具有代表性的分布：开头几课、中段几课和最后几课。
第 3 步：生成 8 道题
基于刚读取的课程内容，恰好生成 8 道选择题：
第 1-4 题：概念题（是什么/为什么） 这些题测试想法、定义和推理的理解。例如：
- “X 的目的是什么？”
- “Z 存在时为什么会发生 Y？”
- “哪项陈述最准确地描述了 A 与 B 的关系？”
- “X 解决了什么问题？”
第 5-8 题：实践题（怎么做/构建） 这些题测试应用知识和实现意识。例如：
- “你会如何实现 X？”
- “哪种方法能正确解决 Y？”
- “构建 Z 的正确步骤顺序是什么？”
- “若训练中观察到 X，应当怎么做？”
每题必须恰有 4 个选项，标记为 A、B、C、D，且只有一个正确选项。错误选项应当可信，但对认真学过材料的人应当明显不对。
给每道题标记其来源课程（例如“第 03 课：矩阵变换”）。
第 4 步：逐题展示
使用 AskUserQuestion 工具（或等效交互式提示）一次展示一道题。格式：
第 1/8 题（概念题）——来自第 03 课：矩阵变换
特征值的几何解释是什么？
A) 矩阵施加的旋转角度
B) 特征向量在变换中被缩放的倍数
C) 变换矩阵的行列式
D) 变换后矩阵的秩等待用户作答后，才进入下一题。
答案隔离
在学习者回答当前题目之前，正确选项和解释必须保持私密。回复格式提示中绝不使用真实答案字母、可能答案或生成的答案分布。若需要纯文本提示，必须严格使用：请只回复一个字母：<A|B|C|D>。
第 5 步：记录与评分
持续记录：
- 8 题中的正确总数
- 每道错题：题号、用户答案、正确答案及来源课程
第 6 步：展示结果
所有 8 题完成后，展示得分和评级：
答对 7-8 题：已掌握
若为第 19 阶段（综合项目）：你已掌握第 19 阶段，也是最后一个阶段。只有能够确认整个课程其余部分均已完成时（当前目录中的 LEARNING.md 路径表显示阶段 0-18 都是 Done 或 Skip），才能再加上 恭喜，你已完成全部课程。单次阶段测验不能证明整个课程已完成。
否则：你对第 N 阶段掌握扎实，可以进入第 N+1 阶段：[下一阶段名称]。
答对 5-6 题：接近掌握
基础扎实。继续前请复习以下具体内容：
随后列出错题关联的课程。
答对 3-4 题：正在形成理解
你的理解正在建立，但还需回顾以下课程：
随后列出每道错题及需重读的课程。
答对 0-2 题：重新开始
这个阶段还需要更多时间。请从头重新学习课程，重点关注：
随后列出所有未掌握的主题。
第 7 步：错题拆解
对用户答错的每一题，展示：
第 N 题：[题目文本，缩写]
你的答案：B
正确答案：C —— [正确选项文本]
原因：[用 1-2 句解释 C 为什么正确]
复习：第 NN 课 —— [课程名称] (phases/<phase-dir>/NN-<lesson-slug>/docs/zh.md)第 8 步：下一步做什么？
最后提供三个选择：
- 重做本测验 —— 从同一阶段生成一组新的 8 道题
- 测试另一阶段 —— 选择其他阶段测试
- 解释一个主题 —— 询问任意错题涉及的概念
等待用户选择后再执行。
规则
- 重考时，在题库耗尽前避免重复题目。题库耗尽后，才可为后续重考重排或改写题目。
- 题目必须直接基于课程文档，不能基于通用知识。
- 用户回答之前，不展示正确答案。
- 学习者回答格式示例中不得出现真实答案字母；使用
<A|B|C|D>作为占位符。 - 题目文本保持简洁，最多一两句话。
- 错误选项必须可信，不要设置玩笑答案。
- 若一个阶段的课程正文待发布（以
docs/zh.md文件为准），告诉用户：第 N 阶段尚未提供课程内容。请选择已完成的阶段进行测验。
© fancyboi999, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/check-understanding of fancyboi999/ai-engineering-from-scratch-zh.
Open the folder on GitHubat commit 94b9888
Compare with similar skills
Check Understanding 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 |
|---|---|---|---|---|---|---|
| Check Understanding this skillfancyboi999/ai-engineering-from-scratch-zh | 1.2k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Codebase Managementgiancarloerra/SocratiCode | 3.3k | 1 repos | ~1.8k | Automated safety check: Pass | AGPL-3.0 | |
| Tool Use Data Synthesissunny-glow/Auto-BenchMax | 1.3k | — | ~3.3k | Automated safety check: Pass | None | |
| Sandbaseiflytek/skillhub | 5.2k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| MCP Local RAGshinpr/mcp-local-rag | 411 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Aisafetyhotwuyoscar/AISafetyHot-Hub | 641 | — | ~1.4k | Automated safety check: Pass | Custom licence |
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交互式测验，将你的 AI/ML 知识映射到 523 节课、20 个阶段的 AI Engineering from Scratch 课程起点。
Claude Certification
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 中四条独立 Claude 认证路线的 AI 原生导师与入门流程。适用于学习者 希望选择 Claude 认证、备考 CCAO-F、CCDV-F、CCAR-F 或 CCAR-P、继续认证路径、以交互方式学习 下一课、运行并验证实践实验、构建并评分产物、参加诊断或模拟测评，或通过 GitHub 上的 Claude Code、…
Course Guide
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 课程的主题路由器。给它一个主题、问题或正在处理的 bug， 它会指出精确教授它的课程，以及下一条正确命令。触发短语： “在哪里学习”、“哪节课涵盖”、“课程导航”、“我卡在”、“接下来该做什么”、 “教我 MCP”、“教我 Agent Skills”、“在哪里准备 Claude certification”，或 "where do I…
Learn
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 课程的交互式课程 tutor。读取 LEARNING.md，获取下一课， 在终端按章节教学，结尾测验并记录进度。可在克隆仓库中或完全通过 raw.githubusercontent.com 工作—— 无需设置。触发短语：“下一课”、“教我”、“继续课程”、“我们来学习”、“继续学习”，或 "next lesson", "teach…
Learn Agent Skills
fancyboi999/ai-engineering-from-scratch-zh
AI Engineering from Scratch 中 Agent Skills Engineering 路线的专注交互 tutor。
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Questions about Check Understanding
What does Check Understanding do?
AI Engineering from Scratch 的阶段测验。用于“给我测验一下”、“测试阶段”、“检查我的理解”、“我掌握第 3 阶段了吗”，也支持 "quiz me", "test phase", "check my understanding", "do I know phase 3" 或 /check-understanding <phase。. Check Understanding is an agent skill from fancyboi999/ai-engineering-from-scratch-zh.
When should I use Check Understanding?
Check Understanding fits situations like: AI & LLM Engineering work in your project.
How do I install Check Understanding in Claude Code?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a claude-code`. Or copy the skill folder (skills/check-understanding in fancyboi999/ai-engineering-from-scratch-zh) into .claude/skills/check-understanding in your project. Claude Code loads it when a task matches its description.
How do I install Check Understanding in Codex?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a codex`. Or copy the skill folder (skills/check-understanding in fancyboi999/ai-engineering-from-scratch-zh) into .agents/skills/check-understanding in your project. Codex loads it when a task matches its description.
Can I use Check Understanding 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 fancyboi999/ai-engineering-from-scratch-zh --skill check-understanding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/check-understanding, .gemini/skills/check-understanding, .github/skills/check-understanding and .opencode/skills/check-understanding in your project.
What does Check Understanding need to run?
SKILL.md names no scripts, command-line tools or credentials: Check Understanding is instructions for the agent only.
Does Check Understanding 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 Check Understanding 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 Check Understanding use?
Check Understanding 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 Check Understanding use?
About 1.1k tokens (SKILL.md is roughly 4.2k 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 Check Understanding?
Skills that share tags, products or a category with Check Understanding: Codebase Management (giancarloerra/SocratiCode, 3.3k stars), Tool Use Data Synthesis (sunny-glow/Auto-BenchMax, 1.3k stars), Sandbase (iflytek/skillhub, 5.2k stars) and MCP Local RAG (shinpr/mcp-local-rag, 411 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Check Understanding?
fancyboi999 (a GitHub user) maintains it in fancyboi999/ai-engineering-from-scratch-zh, which has 1,195 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 9, 2026.
Source: fancyboi999/ai-engineering-from-scratch-zh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.