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Self Assessment

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lhfer
self-assessment

Claude Code 中文自测与学习路径顾问。用于评估当前水平、识别短板、推荐学习顺序。Use when asked to "assess my level", "take the quiz", "find my level", "where should I start", "what should I learn next", "check my skills", "skill check", or similar Chinese requests.

Overview

Publisherlhfer
Repositoryclaude-howto-zh-cn
Skill nameself-assessment
Stars
2.3K
Forks
333
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Self Assessment 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/lhfer/claude-howto-zh-cn/tree/main/.claude/skills/self-assessment
  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/lhfer/claude-howto-zh-cn.git /tmp/claude-howto-zh-cn
mkdir -p .claude/skills
cp -r /tmp/claude-howto-zh-cn/.claude/skills/self-assessment .claude/skills/self-assessment
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Self Assessment 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 Self Assessment 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 Self Assessment 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.

自测与学习路径顾问(Self-Assessment & Learning Path Advisor)

这是一个完整的 Claude Code 交互式自测 skill,用来评估用户在 10 个能力域上的熟练度,并据此生成个性化学习路径。

参考文件

为节省上下文,较长的题目轮次、输出模板和按主题建议拆到了 references/:

  • references/deep-assessment-rounds.md:Deep Assessment 的 5 轮题目与评分映射
  • references/output-templates.md:Quick / Deep 结果和学习路径模板
  • references/topic-recommendations.md:按主题、按得分给出的具体学习建议

执行时先按本文件确定流程;需要展示题目、生成最终报告或补齐主题建议时,再读取对应 reference。不要翻译或改名其中的路径、CLI flags、frontmatter key、JSON/YAML key。

使用说明

Step 1: 先让用户选择评估模式

使用 AskUserQuestion 提供两个选项:

  • Quick Assessment:用 2 道多选题检查 8 个能力项,约 2 分钟,用于快速判断 Beginner / Intermediate / Advanced
  • Deep Assessment:5 轮问题,约 5 分钟,用于分别评估 10 个主题的掌握情况

如果用户选择 Quick Assessment,进入 Step 2A。 如果用户选择 Deep Assessment,进入 Step 2B。


Step 2A:Quick Assessment(快速评估)

使用两个多选问题完成快速自测,每个问题最多 4 个选项。

Question 1(header: 基础) Prompt: 第 1/2 部分:下面哪些 Claude Code 基础能力你已经具备?

Options:

  1. 启动 Claude Code 并对话 — 我会运行 claude 并进入对话
  2. 创建或编辑 CLAUDE.md — 我配置过项目或个人 memory
  3. 使用过 3 个以上 slash commands — 例如 /help、/compact、/model
  4. 创建过 command 或 skill — 写过 SKILL.md 或 .claude/commands/

Question 2(header: 进阶) Prompt: 第 2/2 部分:下面哪些 Claude Code 进阶能力你已经具备?

Options:

  1. 配置过 MCP server — 配置过 GitHub、数据库或其他外部数据源
  2. 设置过 hooks — 配置过 ~/.claude/settings.json 里的 hooks
  3. 创建或使用过 subagents — 使用过 .claude/agents/
  4. 使用过 print mode(claude -p) — 用过非交互模式或 CI/CD 集成

Quick 模式评分:

  • 0-2 项:Level 1 — Beginner
  • 3-5 项:Level 2 — Intermediate
  • 6-8 项:Level 3 — Advanced

进入 Step 3A 输出结果,并列出未勾选项作为短板。


Step 2B:Deep Assessment(深度评估)

Deep 模式共 5 轮,每轮 1 个多选问题,每题最多 4 个选项,每轮覆盖 2 个主题。

完整题面也见 references/deep-assessment-rounds.md。如果本文件与 reference 有冲突,以本文件里的评分规则为准。

第 1 轮:Slash Commands 与 Memory

Header: 命令 Prompt: 下面哪些操作你做过?请选择所有符合的选项。

Options:

  1. 创建过 slash command 或 skill — 写过带 frontmatter 的 SKILL.md 或 .claude/commands/ 文件
  2. 在 command 中使用过动态上下文 — 用过 $ARGUMENTS、$0/$1、!command、@file
  3. 同时配置过项目和个人 memory — 同时配置过项目级和个人级 CLAUDE.md
  4. 使用过 memory 层级功能 — 理解层级优先级、用过 .claude/rules/、path-specific rules 或 @import

Scoring:

  • 1-2 映射到 Slash Commands(0-2)
  • 3-4 映射到 Memory(0-2)
第 2 轮:Skills 与 Hooks

Header: 自动化

Options:

  1. 安装并使用过自动触发的 skill — 使用过会按 description 自动触发的 skill
  2. 控制过 skill 调用方式 — 用过 disable-model-invocation、user-invocable 或 context: fork
  3. 设置过 PreToolUse 或 PostToolUse hook — 配置过常见 hook
  4. 使用过进阶 hook 功能 — 用过 prompt hooks、component-scoped hooks、HTTP hooks、custom JSON output

Scoring:

  • 1-2 映射到 Skills(0-2)
  • 3-4 映射到 Hooks(0-2)
第 3 轮:MCP 与 Subagents

Header: 集成

Options:

  1. 连接过 MCP server 并使用其工具
  2. 使用过进阶 MCP 功能 — project-scope .mcp.json、OAuth、Tool Search、claude mcp serve
  3. 创建或配置过自定义 subagents
  4. 使用过进阶 subagent 功能 — worktree 隔离、persistent memory、background tasks、agent allowlists、agent teams

Scoring:

  • 1-2 映射到 MCP(0-2)
  • 3-4 映射到 Subagents(0-2)
第 4 轮:Checkpoints 与 Advanced Features

Header: 高级

Options:

  1. 用 checkpoints 做过安全试验
  2. 使用过 planning mode 或 extended thinking
  3. 配置过 permission modes
  4. 使用过 remote / desktop / web 功能

Scoring:

  • 1 映射到 Checkpoints(0-1)
  • 2-4 映射到 Advanced Features(0-2,最多记 2 分)
第 5 轮:Plugins 与 CLI

Header: 综合

Options:

  1. 安装或创建过 plugin
  2. 使用过 plugin 进阶功能 — plugin hooks、plugin MCP、LSP、--plugin-dir
  3. 在脚本或 CI/CD 中使用过 print mode
  4. 使用过进阶 CLI 功能 — -c/-r、--agents、--json-schema、--fallback-model、--from-pr

Scoring:

  • 1-2 映射到 Plugins(0-2)
  • 3-4 映射到 CLI(0-2)

进入 Step 3B 输出结果。


Step 3A: Quick 模式结果输出

输出必须包含:

可直接使用 references/output-templates.md 中的 Quick Assessment 结果模板。

markdown
## Claude Code 自测结果

### 你的等级:Level 1 / Level 2 / Level 3

你勾选了 **N/8** 项。

[一句鼓励性的总结]

### 你的能力概览

| 能力领域 | 状态 |
|------|--------|
| 基础 CLI 与对话 | [已掌握 / 有短板] |
| CLAUDE.md 与 Memory | [已掌握 / 有短板] |
| Slash Commands | [已掌握 / 有短板] |
| Custom Commands 与 Skills | [已掌握 / 有短板] |
| MCP | [已掌握 / 有短板] |
| Hooks | [已掌握 / 有短板] |
| Subagents | [已掌握 / 有短板] |
| Print Mode 与 CI/CD | [已掌握 / 有短板] |

### 主要短板

[对每个未勾选项,给一行说明 + 对应教程链接]

### 个性化学习路径

[按 Step 4 生成]

Step 3B: Deep 模式结果输出

Deep 模式要输出完整结果:

可直接使用 references/output-templates.md 中的 Deep Assessment 结果模板。

markdown
## Claude Code 自测结果

### 整体等级:[Level 1 / Level 2 / Level 3]

**总分:N/19**

[一句鼓励性总结]

### 你的能力画像

| 功能领域 | 得分 | 掌握程度 | 状态 |
|-------------|-------|---------|--------|
| Slash Commands | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Memory | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Skills | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Hooks | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| MCP | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Subagents | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Checkpoints | N/1 | 未掌握 / 熟练(None / Proficient) | 学习 / 已掌握(Learn / Mastered) |
| Advanced Features | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| Plugins | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |
| CLI | N/2 | 未掌握 / 基础 / 熟练(None / Basic / Proficient) | 学习 / 复习 / 已掌握(Learn / Review / Mastered) |

然后继续输出:

  • 优势领域:得分满分的主题
  • 优先补齐短板:得分 0 的主题,按依赖顺序排列
  • 需要复习的领域:得分 1 的主题
  • 你的个性化学习路径

Deep 模式总体等级:

  • 0-6:Level 1
  • 7-13:Level 2
  • 14-19:Level 3

Step 4: 生成个性化学习路径

不要简单重复通用路线,要按短板动态生成。

具体主题建议优先参考 references/topic-recommendations.md,但要根据用户实际勾选结果裁剪,不要把所有主题机械列出来。

规则:

  1. 满分主题不再列为重点学习项
  2. 按依赖顺序排学习路径:
    • Slash Commands → Skills
    • Memory → Subagents
    • Hooks 依赖 Slash Commands
    • Plugins 依赖 MCP、Skills、Hooks
    • Advanced Features 依赖前面大多数基础
  3. 得分 1 的主题推荐“深入补课”
  4. 按还没掌握的主题估算总时长
  5. 路径分成 2-3 个 phase

输出格式:

markdown
### 你的个性化学习路径

**预计时间**:约 N 小时

#### 阶段 1:[名称](约 N 小时)

**[主题]** — [从零学习 / 深入补课]
- 教程:[链接]
- 重点关注:[章节]
- 关键练习:[一个练习]
- 完成标准:[成功条件]

Step 5: 提供后续动作

结果给完后,再用 AskUserQuestion 让用户选择:

  1. 从第一个短板开始
  2. 深入学习一个主题
  3. 搭建练习项目
  4. 重新评估

如果用户选第一项:直接进入第一个短板主题的学习建议。 如果用户选第二项:让用户选一个主题并解释。 如果用户选第三项:根据短板组合一个练习项目。 如果用户选第四项:重新开始。

输出要求

  • 全程使用中文
  • 保留关键英文术语,例如 skills、MCP、CLI
  • 不要空泛鼓励,要给可执行建议
  • 教程引用优先指向仓库内对应 lesson

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 Self Assessment AI skill do?

Claude Code 中文自测与学习路径顾问。用于评估当前水平、识别短板、推荐学习顺序。Use when asked to "assess my level", "take the quiz", "find my level", "where should I start", "what should I learn next", "check my skills", "skill check", or similar Chinese requests.

Why use Self Assessment on TypingMind?

Because you install it once and use it with any model. Self Assessment 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 Self Assessment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lhfer/claude-howto-zh-cn/tree/main/.claude/skills/self-assessment. 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 Self Assessment?

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 Self Assessment?

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

Is the Self Assessment AI skill free?

Yes. It is published on GitHub by lhfer 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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