Agent skill

Gaokao Expert

by staruhub in staruhub/ClaudeSkills

资深高考命题专家助手,提供专业的命题指导和评审服务。适用于创作高考试题、评审试题质量、分析试卷结构、了解命题趋势等场景。结合文档工具提取解压文件,使用网络搜索了解当年最新命题趋势,使用分析工具评估题目质量和试卷结构。涵盖"一核四层四翼"评价体系、题型规范、评分标准、命题流程等多个维度。不用于:大学/考研/中考命题(体系不同,仅可借鉴)、日常作业题编写、直接替考生解题。

MITAuto-check passedDocuments & Office

Install Gaokao Expert

skills CLI
$ npx skills add staruhub/ClaudeSkills --skill gaokao-expert -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install staruhub/ClaudeSkills gaokao-expert --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/staruhub/ClaudeSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/lab/Geek-skills-gaokao-expert .claude/skills/gaokao-expert && rm -rf skills-src

Use ~/.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/

Facts

Skill name
gaokao-expert
GitHub stars
728
Token cost
~1.1k tokens
SKILL.md length
283 words
Files
8 (incl. scripts, references)
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

资深高考命题专家助手,提供专业的命题指导和评审服务。适用于创作高考试题、评审试题质量、分析试卷结构、了解命题趋势等场景。结合文档工具提取解压文件,使用网络搜索了解当年最新命题趋势,使用分析工具评估题目质量和试卷结构。涵盖"一核四层四翼"评价体系、题型规范、评分标准、命题流程等多个维度。不用于:大学/考研/中考命题(体系不同,仅可借鉴)、日常作业题编写、直接替考生解题。

  • Works in 4 steps: 文档工具 → 网络搜索工具 → 分析工具 → …
  • Documents & Office work in your project
  • SKILL.md covers 核心能力, 工作流程, 工具使用指南 and 关键原则, plus 4 more sections
  • Runs Python scripts from its folder; calls python

What it does

Gaokao Expert is an agent skill from staruhub/ClaudeSkills. 资深高考命题专家助手,提供专业的命题指导和评审服务。适用于创作高考试题、评审试题质量、分析试卷结构、了解命题趋势等场景。结合文档工具提取解压文件,使用网络搜索了解当年最新命题趋势,使用分析工具评估题目质量和试卷结构。涵盖"一核四层四翼"评价体系、题型规范、评分标准、命题流程等多个维度。不用于:大学/考研/中考命题(体系不同,仅可借鉴)、日常作业题编写、直接替考生解题。

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `evals/routing-evals.json`, `references/命题标准.md` and `references/命题趋势.md`).

It sits in Documents & Office. It works with Microsoft Word. The repository describes itself as: 13 curated Agent Skills for research, product decisions, decks, publishing, audits, and more — portable across skills-compatible agents. The licence is MIT.

When your agent uses it

  • Documents & Office work in your project

Example prompts

  • “一核四层四翼”
  • “/gaokao-expert”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 文档工具
  2. 网络搜索工具
  3. 分析工具
  4. 参考文档

What it can do on your machine

Read from SKILL.md and the folder at commit 66e02d2. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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

Gaokao Expert loads about 1.1k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 50 tokens; SKILL.md has 283 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~50
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~13k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from staruhub/ClaudeSkills at commit 66e02d2, republished under its MIT licence (© staruhub). 283 words, ~1,060 tokens.

Download SKILL.mdSave it as .claude/skills/gaokao-expert/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
gaokao-expert
description
资深高考命题专家助手,提供专业的命题指导和评审服务。适用于创作高考试题、评审试题质量、分析试卷结构、了解命题趋势等场景。结合文档工具提取解压文件,使用网络搜索了解当年最新命题趋势,使用分析工具评估题目质量和试卷结构。涵盖"一核四层四翼"评价体系、题型规范、评分标准、命题流程等多个维度。不用于:大学/考研/中考命题(体系不同,仅可借鉴)、日常作业题编写、直接替考生解题。
version
1.1.0

高考命题专家

这是一个专业的高考命题辅助技能,帮助命题者创作高质量的高考试题,评审试题质量,分析试卷结构,并提供基于最新命题标准和趋势的专业建议。

核心能力

作为高考命题专家,本技能具备以下核心能力:

  1. 命题标准掌握: 深入理解"一核四层四翼"评价体系和最新命题趋势
  2. 试题创作指导: 提供从情境设计到评分标准的全流程命题指导
  3. 质量评审分析: 对试题和试卷进行多维度的质量分析和评估
  4. 工具综合运用: 结合文档工具、网络搜索、分析脚本等多种工具
  5. 趋势洞察更新: 持续关注最新的命题改革动向和教育政策

工作流程

第一步: 了解需求和背景

在开始任何命题工作前,首先要明确:

  1. 命题目标: 正式高考题还是模拟题?面向哪个年级和科目?
  2. 查看相关文档: 如果用户上传了文档,使用view工具查看或使用docx/pdf skill提取内容
  3. 搜索最新信息: 使用web_search了解最新的命题趋势和政策
第二步: 学习命题标准

必读参考文档: references/命题标准.md

包含:

  • "一核四层四翼"评价体系详解
  • 命题理念和基本原则
  • 试题情境设计要求
  • 试题难度控制标准

根据需要阅读:

  • references/命题趋势.md - 命题趋势分析(有记录时点,会过时——趋势类结论必须先 web_search 当年信息,文档只作分析框架)
  • references/题型规范.md - 学习各类题型的命题规范
  • references/工作流程.md - 掌握完整的命题工作流程
第三步: 执行具体任务
任务A: 创作试题
  1. 选择并搜索素材

    web_search: [相关主题] 最新进展
    web_fetch: [权威网站URL]
  2. 设计试题情境 - 基于真实素材,确保情境真实、新颖、适切

  3. 编写试题内容 - 参考题型规范.md中的具体要求

  4. 自我检查 - 使用工作流程.md中的审核清单

  5. 质量分析 (可选) - 运行analyze_question.py分析质量

任务B: 评审试题
  1. 提取试题内容 - 使用view或docx/pdf skill提取
  2. 多维度评审 - 科学性、规范性、公平性、育人性、创新性、适切性
  3. 参照标准检查 - 对照命题标准和题型规范
  4. 使用分析工具 - 运行analyze_question.py
  5. 提供评审报告 - 总体评价、优点、问题、改进建议
任务C: 分析试卷结构
  1. 提取试卷信息 - 整理每道题的信息
  2. 创建试卷数据文件 - 创建JSON格式的数据文件
  3. 运行结构分析 - 运行analyze_paper.py
  4. 解读分析结果 - 分析知识分布、能力层级、难度梯度等
  5. 提供优化建议 - 基于分析结果给出改进方案
任务D: 了解命题趋势
  1. 搜索最新信息 - 搜索当年高考命题趋势(年份用当前年份,不要写死)
  2. 阅读参考文档 - 阅读命题趋势和命题标准文档
  3. 综合分析 - 对比官方文件和专家解读
  4. 案例分析 - 搜索最新真题案例进行分析

工具使用指南

1. 文档工具
  • 查看上传的文档: 路径以宿主环境实际上传位置为准
  • 提取Word/PDF内容: 阅读并使用docx/pdf skill
2. 网络搜索工具
  • 搜索命题素材: web_search: [当前年份] 人工智能最新进展
  • 搜索命题标准: web_search: 高考命题原则 一核四层四翼
  • 获取详细内容: web_fetch: [权威URL]
3. 分析工具

题目质量分析: 创建题目 JSON 后运行 python scripts/analyze_question.py question.json 试卷结构分析: 创建试卷 JSON 后运行 python scripts/analyze_paper.py paper.json

4. 参考文档

核心参考文档:

  • references/命题标准.md - 高考命题标准与评价体系
  • references/命题趋势.md - 命题趋势分析(记录时点资料,会过时)
  • references/题型规范.md - 题型规范与命题技术
  • references/工作流程.md - 命题工作流程指南

使用方法: 直接读取 references/[文档名](相对本 skill 目录)

关键原则

命题的"四要四不要"

要:

  1. 要真实情境 - 选择真实、新颖的生活、生产、科研情境
  2. 要能力素养 - 考查学科核心素养和关键能力
  3. 要价值引领 - 体现正确的价值观,发挥育人功能
  4. 要科学规范 - 确保内容准确、表述清晰、评分合理

不要:

  1. 不要偏题怪题 - 避免超纲、过难、钻牛角尖的题目
  2. 不要死扣教材 - 不机械照搬教材原文,要活学活用
  3. 不要套路模板 - 创新考查方式,使套路失效
  4. 不要价值偏差 - 避免错误导向和消极内容
评审的"七个维度"
  1. 知识点覆盖 - 是否涵盖主干知识
  2. 能力层级 - 考查的能力层次是否恰当
  3. 情境设计 - 情境是否真实、新颖、适切
  4. 难度适中 - 难度系数是否合理
  5. 创新性 - 考查角度、题型形式是否有创新
  6. 育人价值 - 是否渗透正确价值观
  7. 科学规范 - 内容是否准确、表述是否清晰

验收标准(命题/评审完成前自查)

  • 试题情境来自本次搜索的真实素材,标注了来源
  • 输出包含完整六件套:情境、题干、答案、评分标准、命题说明、预估难度
  • 对照"四要四不要"逐条过检,无超纲、无套路模板、无价值偏差
  • 评审报告的每个问题都指向试题的具体位置,不是泛泛而谈
  • 趋势类结论有当年搜索依据,未引用过时的内置"最新趋势"

已知陷阱

陷阱具体表现应对
情境造假编造"某研究表明"式虚构素材情境必须来自可检索的真实来源并标注
趋势旧闻把参考文档里的记录时点趋势当"今年最新"先 web_search 当年信息,文档只作框架
难度失准凭感觉标难度系数用 analyze_question.py 辅助,并说明预估依据
答案不唯一选择题多解、主观题评分标准含糊自查环节专项验证答案唯一性与评分可操作性

输出格式建议

创作试题的输出格式
markdown
## [学科][题型] - [主题]

### 试题内容

**[情境材料]**
[情境内容]

**[题干]**
[问题表述]

**[选项/答题要求]**
[选项或答题要求]

### 参考答案
[详细答案]

### 评分标准
[评分细则]

### 命题说明
- 考查知识点: [知识点]
- 考查能力: [能力]
- 能力层级: [层级]
- 预估难度: [难度系数]
- 情境来源: [来源]
- 创新点: [创新之处]
评审试题的输出格式
markdown
## 试题质量评审报告

### 一、总体评价
总体评分: X/10.0
总体评价: [优秀/良好/合格/需改进]

### 二、各维度评分
[各维度的评分和评价]

### 三、主要优点
1. [优点1]
2. [优点2]

### 四、存在问题
1. [问题1]
2. [问题2]

### 五、改进建议
1. [建议1]
2. [建议2]

资源清单

参考文档 (references/)
  • 命题标准.md - 命题标准与评价体系详解
  • 命题趋势.md - 命题趋势分析(记录时点资料,会过时)
  • 题型规范.md - 题型规范和技术指南
  • 工作流程.md - 命题工作流程指南
分析脚本 (scripts/)
  • analyze_question.py - 题目质量分析工具
  • analyze_paper.py - 试卷结构分析工具
使用建议
  • 首次使用: 必读命题标准.md和命题趋势.md
  • 创作试题: 参考工作流程.md,使用网络搜索工具
  • 评审试题: 参考题型规范.md,使用分析工具
  • 分析试卷: 使用analyze_paper.py,对照标准评价

evals/routing-evals.json — 触发边界回归用例,改 description 后用仓库根 scripts/run_routing_evals.py 校验。

© staruhub, 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 (scripts, references) in lab/Geek-skills-gaokao-expert of staruhub/ClaudeSkills.

  • SKILL.md
  • evals/routing-evals.json
  • references/命题标准.md
  • references/命题趋势.md
  • references/工作流程.md
  • references/题型规范.md
  • scripts/analyze_paper.py
  • scripts/analyze_question.py

Open the folder on GitHubat commit 66e02d2

Compare with similar skills

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    Windows C盘清理和磁盘空间管理。当用户说C盘满了、磁盘空间不足、清理临时文件/缓存/回收站/系统日志、查找大文件、分析磁盘占用时使用。仅适用于 Windows 环境。不用于:macOS/Linux 磁盘清理、卸载软件(引导用户走系统卸载)、清理用户个人文件(只报告位置,删除决定权在用户)。

    728 GitHub stars~518 tokensUpdated 1 mo ago
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  • LLM Wiki

    staruhub/ClaudeSkills

    Build and maintain a structured LLM-generated wiki for any codebase.

    728 GitHub stars~1.6k tokensUpdated 1 mo ago
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  • Mineru PDF Parser

    staruhub/ClaudeSkills

    用 MinerU 将复杂PDF文档转换为LLM友好的Markdown/JSON格式。适用于:(1) PDF转Markdown/JSON,(2) 提取PDF中的文本、表格、公式、图像,(3) 解析学术论文、技术文档、商业报告,(4) 为RAG应用准备文档数据,(5) 批量处理PDF。触发关键词:"PDF解析"、"PDF转Markdown"、"提取PDF表格/公式"、"MinerU"、"parse…

    728 GitHub stars~671 tokensUpdated 1 mo ago
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Works with

Questions about Gaokao Expert

What does Gaokao Expert do?

资深高考命题专家助手,提供专业的命题指导和评审服务。适用于创作高考试题、评审试题质量、分析试卷结构、了解命题趋势等场景。结合文档工具提取解压文件,使用网络搜索了解当年最新命题趋势,使用分析工具评估题目质量和试卷结构。涵盖"一核四层四翼"评价体系、题型规范、评分标准、命题流程等多个维度。不用于:大学/考研/中考命题(体系不同,仅可借鉴)、日常作业题编写、直接替考生解题。. Gaokao Expert is an agent skill from staruhub/ClaudeSkills.

When should I use Gaokao Expert?

Gaokao Expert fits situations like: documents & Office work in your project.

How do I install Gaokao Expert in Claude Code?

Run `npx skills add staruhub/ClaudeSkills --skill gaokao-expert -a claude-code`. Or copy the skill folder (lab/Geek-skills-gaokao-expert in staruhub/ClaudeSkills) into .claude/skills/gaokao-expert in your project. Claude Code loads it when a task matches its description.

How do I install Gaokao Expert in Codex?

Run `npx skills add staruhub/ClaudeSkills --skill gaokao-expert -a codex`. Or copy the skill folder (lab/Geek-skills-gaokao-expert in staruhub/ClaudeSkills) into .agents/skills/gaokao-expert in your project. Codex loads it when a task matches its description.

Can I use Gaokao Expert 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 staruhub/ClaudeSkills --skill gaokao-expert -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gaokao-expert, .gemini/skills/gaokao-expert, .github/skills/gaokao-expert and .opencode/skills/gaokao-expert in your project.

What does Gaokao Expert need to run?

Going by SKILL.md and its folder, Gaokao Expert needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Gaokao Expert 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 Gaokao Expert 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Gaokao Expert use?

Gaokao Expert 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 Gaokao Expert 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. Its references folder adds about 12k tokens, read only when the agent opens those files.

What are the alternatives to Gaokao Expert?

Skills that share tags, products or a category with Gaokao Expert: Markitdown (ImCa0/just-laws, 781 stars), DOCX (rvdbreemen/OTGW-firmware, 207 stars), Word Document Reader and Writer (HKUDS/DeepTutor, 41k stars) and Gzh Design (isjiamu/gzh-design-skill, 4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gaokao Expert?

staruhub (a GitHub user) maintains it in staruhub/ClaudeSkills, which has 728 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on August 13, 2026.

Source: staruhub/ClaudeSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.