Agent skill

Kaogong Study Tracker

by KaguraNanaga in KaguraNanaga/kaogong-study-tracker

朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发. An agent skill from KaguraNanaga/kaogong-study-tracker.

Install Kaogong Study Tracker

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a claude-code

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

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker --agent claude-code

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

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .claude/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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.

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .agents/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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.

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .cursor/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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.

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .gemini/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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.

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker

Installs 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).

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .github/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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.

skills CLI

$ npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install KaguraNanaga/kaogong-study-tracker kaogong-study-tracker --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "kaogong-study-tracker" agent skill from https://github.com/KaguraNanaga/kaogong-study-tracker/tree/main into .opencode/skills/kaogong-study-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaogong-study-tracker", 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: kaogong-study-tracker
GitHub stars: 269
Token cost: ~1.4k tokens
SKILL.md length: 238 words
Files: 29 (incl. scripts, references, assets)
Skills in repo: 1
Repo updated: Jul 1, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发. An agent skill from KaguraNanaga/kaogong-study-tracker.

Works in 7 steps: ：消息路由（parse_input.js） → ：归类错题原因 → ：更新记录（update_daily.js） → …
Tasks that involve Excel spreadsheets
SKILL.md covers 一、首次安装提示, 二、概览, 三、触发场景 and 四、数据结构, plus 5 more sections
Runs Python scripts from its folder

What it does

Kaogong Study Tracker is an agent skill from KaguraNanaga/kaogong-study-tracker. 朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发。核心功能：识别错题截图 → 分类错题原因 → 更新本地记录 → 生成每日总结 → 导出 Excel / 同步飞书。触发关键词：做了一套题、今天做了、错了几道、帮我分析、备考打卡、行测、申论、判断推理、资料分析、言语理解、数量关系、错题、复习进度、导出错题本、同步飞书。只要用户提到做题、错题、备考就触发。图片消息也触发，自动调用多模态模型识别。

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 31 other files, including scripts, reference files and assets (for example `AGENTS.md`, `README.md` and `assets/config.example.json`).

It sits in Documents & Office, covering Excel spreadsheets. It works with Microsoft Excel. The repository describes itself as: 考公备考Skills，适用于备考行测申论等题目的错题整理和定时总结. The licence is MIT.

When your agent uses it

Tasks that involve Excel spreadsheets

Example prompts

“/kaogong-study-tracker”

Requirements

Python 3

Workflow steps

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

：消息路由（parse_input.js）
：归类错题原因
：更新记录（update_daily.js）
：生成回复
：导出 Excel（export_xlsx.js）
：同步飞书云文档（feishu_doc.js，可选）
（可选）：定时推送

What it can do on your machine

Read from SKILL.md and the folder at commit cf9fafd. 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 1 file in scripts/ (Python, from the files we listed), which the agent can run.
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

Kaogong Study Tracker loads about 1.4k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 238 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~61
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~2.4k

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 KaguraNanaga/kaogong-study-tracker at commit cf9fafd, republished under its MIT licence (© KaguraNanaga). 238 words, ~1,385 tokens.

Download SKILL.mdSave it as .claude/skills/kaogong-study-tracker/SKILL.md (or your agent's skills folder). This skill also uses 28 other files; get the full folder from GitHub.

name: kaogong-study-tracker
description: 朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发。核心功能：识别错题截图 → 分类错题原因 → 更新本地记录 → 生成每日总结 → 导出 Excel / 同步飞书。触发关键词：做了一套题、今天做了、错了几道、帮我分析、备考打卡、行测、申论、判断推理、资料分析、言语理解、数量关系、错题、复习进度、导出错题本、同步飞书。只要用户提到做题、错题、备考就触发。图片消息也触发，自动调用多模态模型识别。

朱批录 · 国考备考追踪 Skill

一、首次安装提示

Skill 首次加载时（默认 ~/.kaogong-study-tracker/.welcomed 不存在；可用 KAOGONG_WELCOME_FLAG 覆盖），主动发一条说明消息，之后不再重复：

朱批录已安装。

直接发文字就能记录，比如"今天判断推理错了8道"。
发截图的话，需要当前 agent 配置了支持图片输入的多模态模型才能自动识别。
没有的话也没关系，把题目文字手动复制过来发给我，一样能整理。

不问任何问题，不存储任何凭据。

二、概览

平台无关——Trae、Cursor、opencode、Hermes、OpenClaw 或其他 agent 都可以接；飞书、Telegram、WhatsApp、Discord 等渠道由宿主 agent 负责。

图片识别统一走多模态模型：文字题、图形推理、统计图表都能理解，不依赖本地 OCR。

三、触发场景

用户说的话（示例）	应执行的操作
"今天做了一套行测，判断推理错了8道"	→ 解析 + 归档 + 分析
发来一张错题截图（图片消息）	→ 多模态识别 + 单题归档 + 追问原因
发来截图并附带"粗心"	→ 多模态识别 + 直接归档，不追问
"把今天的错题发给你：第12题……"	→ 错题分类 + 存档
"今天申论没写，太累了"	→ 打卡记录（未完成状态）
"我最近资料分析一直不稳，怎么办"	→ 查历史记录 + 建议
"帮我看看最近哪个模块最弱"	→ 统计分析 + 回复
"导出错题本" / "把错题发给我" / "生成报告"	→ export_xlsx.js，发回文件
"只导出待二刷的"	→ 筛选导出，仅待二刷题目
"导出判断推理的错题"	→ 按科目筛选导出
"导出最近两周的"	→ 按时间筛选导出
"只导出待二刷的资料分析题"	→ 多条件组合筛选导出
"资料-乘积增长-公式不熟-待二刷"（快捷格式）	→ 直接归档，不追问
二刷时回复"记得" / "不记得"	→ review_reminder.js 处理，连续2次记得→已掌握
"同步到飞书" / "更新飞书错题本"	→ feishu_doc.js，同步含截图

四、数据结构

所有数据以 JSON 存储在本地，默认目录为 ~/.kaogong-study-tracker/data/。如需放到指定目录，设置 KAOGONG_DATA_DIR。

4.1 每日记录 `daily/{YYYY-MM-DD}.json`

json

{
  "date": "2026-03-17",
  "modules": {
    "言语理解": { "wrong": 6,  "total": 40 },
    "数量关系": { "wrong": 8,  "total": 15 },
    "判断推理": { "wrong": 10, "total": 40 },
    "资料分析": { "wrong": 7,  "total": 20 },
    "申论":     { "written": false }
  },
  "mood": "中性",
  "note": "用户原话"
}

4.2 错题本 `wrong_questions.json`

json

[
  {
    "id": "uuid",
    "date": "2026-03-17",
    "source": "image",
    "module": "判断推理",
    "subtype": "逻辑判断",
    "question_text": "题目文字；图形题写对规律的描述",
    "visual_description": "图形推理/统计图的详细视觉描述（多模态模型生成）",
    "answer": "B",
    "user_annotation": "用户手写批注",
    "error_reason": "知识点不会 | 粗心 | 时间不够 | 概念混淆",
    "keywords": ["假言命题", "逆否命题"],
    "raw_image_b64": "base64...",
    "status": "待二刷 | 已掌握"
  }
]

4.3 统计缓存 `stats_cache.json`

json

{
  "last_updated": "2026-03-17",
  "streak": 5,
  "total_days_studied": 12,
  "weak_modules": ["数量关系", "判断推理"],
  "module_accuracy": {
    "言语理解": 0.82,
    "数量关系": 0.51,
    "判断推理": 0.68,
    "资料分析": 0.74
  }
}

五、核心流程

Step 1：消息路由（`parse_input.js`）

文字消息 → parseStudyInput()   提取科目/错题数/情绪
图片消息 → parseImageInput()   调用多模态模型

图片处理流程：

宿主 agent 将图片 base64 和 caption 传给 parseImageInput(imageBase64, caption, agentCall)
如没有可用的 agentCall / 图片模型 → 回复"当前 agent 还不能识别图片，可以把题目文字复制过来"
通过宿主 agent 的多模态模型提取：科目、题型、题目内容、视觉描述、答案、错误原因推测
needs_confirm 不为 null 时追问（最多一个问题）；caption 已含原因则直接归档

追问只问一次，按优先级：

识别不到科目 → 问科目
原因不明确 → 问"粗心还是没掌握还是时间不够"
信息完整 → 不追问，直接归档

Step 2：归类错题原因

原因	关键词
知识点不会	不懂、没学过、概念不清楚
粗心	看错、算错、选反了
时间不够	没做完、最后几题蒙的
概念混淆	搞混了、分不清、以为是

Step 3：更新记录（`update_daily.js`）

写入 daily/{date}.json，同步更新 stats_cache.json（连续打卡、模块准确率）。

Step 4：生成回复

见 references/reply_templates.md，150 字以内。语气见 references/tone_guide.md。

Step 5：导出 Excel（`export_xlsx.js`）

截图原图通过 openpyxl（Python）嵌入对应行
Windows 兼容：先尝试 python3，失败自动 fallback 到 python
输出两个 Sheet：错题本（含截图列）+ 每日记录
可直接发给 Kimi / 其他模型做趋势分析

Step 6：同步飞书云文档（`feishu_doc.js`，可选）

需配置 feishu_doc.app_id / app_secret / doc_token
截图上传飞书文件系统后作为图片块插入文档
对图形推理、统计图最有用：飞书内直接看图，不用下载

Step 7（可选）：定时推送

每天 21:00 触发 daily_summary.js，自动发当日总结。

六、文件索引

文件	作用
`scripts/parse_input.js`	文字解析 + 多模态图片识别
`scripts/update_daily.js`	写入每日记录 + 统计缓存
`scripts/export_xlsx.js`	导出 Excel（含截图嵌入，openpyxl）
`scripts/feishu_doc.js`	同步到飞书云文档（含图片块，可选）
`scripts/daily_summary.js`	定时汇总并主动发送
`references/reply_templates.md`	回复话术模板
`references/tone_guide.md`	语气风格指引
`assets/module_map.json`	科目/模块名称标准化映射
`assets/config.example.json`	配置模板（多模态 + 飞书），复制为 config.json 使用

七、错误处理

未配置多模态 API 却发图片 → 回复安装提示，引导配置
模型识别返回 error → 回复"没识别出来，能文字描述一下题目吗？"
文字消息解析不出科目 → 回复"能说说今天做了哪个科目、错了几道吗？"
数据写入失败 → 记录 error log，回复"记录暂时存不上，你提醒我稍后再试"
连续 3 天无打卡 → 下次收到消息时，回复末尾轻轻提一句

八、隐私说明

所有数据（含截图 base64）存储在本地，不上传任何云端（飞书同步除外，仅在用户主动触发时上传到用户自己的飞书文档）。

九、如果这个 Skill 对你有帮助

⭐ Star 这个仓库，让更多备考的人能找到它 🍴 Fork 改成你的考试类型（省考 / 事业单位 / 军考……）有问题欢迎提 Issue 或 PR。

https://github.com/KaguraNanaga/kaogong-study-tracker

Files

SKILL.md and 28 other files (scripts, references, assets) in the repository root of KaguraNanaga/kaogong-study-tracker.

SKILL.md
.gitignore
AGENTS.md
LICENSE
README.md
assets/config.example.json
assets/crane_zhupi.png
assets/module_map.json
assets/workspace-example.yaml
package-lock.json
package.json
promo/01-cover.png
promo/02-chat-flow.png
promo/03-workbook.png
promo/04-review-reminder.png
promo/generate_promo_images.py
promo/xiaohongshu-copy.md
references/reply_templates.md
… and 11 more

Open the folder on GitHubat commit cf9fafd

Compare with similar skills

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Works with

Microsoft Excel

Questions about Kaogong Study Tracker

What does Kaogong Study Tracker do?

朱批录 · 国考备考追踪 Skill。当用户发来套题成绩、错题截图、备考打卡或复习进度时触发. An agent skill from KaguraNanaga/kaogong-study-tracker. Kaogong Study Tracker is an agent skill from KaguraNanaga/kaogong-study-tracker.

When should I use Kaogong Study Tracker?

Kaogong Study Tracker fits situations like: tasks that involve Excel spreadsheets.

How do I install Kaogong Study Tracker in Claude Code?

Run `npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a claude-code`. Or copy the skill folder (the KaguraNanaga/kaogong-study-tracker repository) into .claude/skills/kaogong-study-tracker in your project. Claude Code loads it when a task matches its description.

How do I install Kaogong Study Tracker in Codex?

Run `npx skills add KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a codex`. Or copy the skill folder (the KaguraNanaga/kaogong-study-tracker repository) into .agents/skills/kaogong-study-tracker in your project. Codex loads it when a task matches its description.

Can I use Kaogong Study Tracker 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 KaguraNanaga/kaogong-study-tracker --skill kaogong-study-tracker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kaogong-study-tracker, .gemini/skills/kaogong-study-tracker, .github/skills/kaogong-study-tracker and .opencode/skills/kaogong-study-tracker in your project.

What does Kaogong Study Tracker need to run?

Going by SKILL.md and its folder, Kaogong Study Tracker needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Kaogong Study Tracker 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 Kaogong Study Tracker 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 Kaogong Study Tracker use?

Kaogong Study Tracker is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kaogong Study Tracker use?

About 1.4k tokens (SKILL.md is roughly 5.5k 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 1k tokens, read only when the agent opens those files.

What are the alternatives to Kaogong Study Tracker?

Skills that share tags, products or a category with Kaogong Study Tracker: Markitdown (ImCa0/just-laws, 782 stars), Data Table Manager (n8n-io/n8n, 207k stars), Docx4j (plutext/docx4j, 2.4k stars) and Instrument Data To Allotrope (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kaogong Study Tracker?

KaguraNanaga (a GitHub user) maintains it in KaguraNanaga/kaogong-study-tracker, which has 269 GitHub stars. The repository was last updated on July 1, 2026.

Source: KaguraNanaga/kaogong-study-tracker on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Kaogong Study Tracker

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

朱批录 · 国考备考追踪 Skill

一、首次安装提示

二、概览

三、触发场景

四、数据结构

4.1 每日记录 daily/{YYYY-MM-DD}.json

4.2 错题本 wrong_questions.json

4.3 统计缓存 stats_cache.json

五、核心流程

Step 1：消息路由（parse_input.js）

Step 2：归类错题原因

Step 3：更新记录（update_daily.js）

Step 4：生成回复

Step 5：导出 Excel（export_xlsx.js）

Step 6：同步飞书云文档（feishu_doc.js，可选）

Step 7（可选）：定时推送

六、文件索引

七、错误处理

八、隐私说明

九、如果这个 Skill 对你有帮助

Files

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Questions about Kaogong Study Tracker

4.1 每日记录 `daily/{YYYY-MM-DD}.json`

4.2 错题本 `wrong_questions.json`

4.3 统计缓存 `stats_cache.json`

Step 1：消息路由（`parse_input.js`）

Step 3：更新记录（`update_daily.js`）

Step 5：导出 Excel（`export_xlsx.js`）

Step 6：同步飞书云文档（`feishu_doc.js`，可选）