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.
npx skills add staruhub/ClaudeSkills --skill geek-skills-gaokao-expertgit clone --depth 1 https://github.com/staruhub/ClaudeSkillsWrote 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.
[](https://agentmods.dev/skills/staruhub/claudeskills/geek-skills-gaokao-expert)<a href="https://agentmods.dev/skills/staruhub/claudeskills/geek-skills-gaokao-expert"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-gaokao-expert/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.
<a href="https://agentmods.dev/skills/staruhub/claudeskills/geek-skills-gaokao-expert"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-gaokao-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00150 | $0.02570 |
| Opus 5 | $0.00075 | $0.01285 |
| Sonnet 5 | $0.00030 | $0.00514 |
| Haiku 4.5 | $0.00015 | $0.00257 |
Grade A, and why
gaokao-expert 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- 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
- 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
- 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
- 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
- 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:
- 命题目标: 正式高考题还是模拟题?面向哪个年级和科目?
- 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
- 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
-
选择并搜索素材
web_search: [相关主题] 最新进展 web_fetch: [权威网站URL] -
设计试题情境 - 基于真实素材,确保情境真实、新颖、适切
-
编写试题内容 - 参考
题型规范.md中的具体要求 -
自我检查 - 使用
工作流程.md中的审核清单 -
质量分析 (可选) - 运行analyze_question.py分析质量
任务B: 评审试题
- 提取试题内容 - 使用view或docx/pdf skill提取
- 多维度评审 - 科学性、规范性、公平性、育人性、创新性、适切性
- 参照标准检查 - 对照命题标准和题型规范
- 使用分析工具 - 运行analyze_question.py
- 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
- 提取试卷信息 - 整理每道题的信息
- 创建试卷数据文件 - 创建JSON格式的数据文件
- 运行结构分析 - 运行analyze_paper.py
- 解读分析结果 - 分析知识分布、能力层级、难度梯度等
- 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
- 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）
- 阅读参考文档 - 阅读命题趋势和命题标准文档
- 综合分析 - 对比官方文件和专家解读
- 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
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.
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.
- 13d ago First seen · 235 lines · 150 tokens per session scan A 69fb8741b92a
gaokao-expert is a skill published in the GitHub repository staruhub/ClaudeSkills (712 stars, last pushed 1mo ago), licensed MIT. It adds 150 tokens to every session and 2,570 once invoked, about $0.0007 per session on Opus 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.
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