Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/cuic19053-hue/-skills-/major_transfer)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/major_transfer"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/major_transfer/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/cuic19053-hue/-skills-/major_transfer"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/major_transfer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00195 | $0.23457 |
| Opus 5 | $0.00097 | $0.11729 |
| Sonnet 5 | $0.00039 | $0.04691 |
| Haiku 4.5 | $0.00019 | $0.02346 |
Grade A, and why
major_transfer 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 9d 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 — 1,301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
转专业申请书 Skill
本 skill 处理"转专业申请书""转系申请书""专业调整申请"全流程：信息采集 → 书信体撰写 → docx 生成 → 质检。
核心定位：转专业是大学本科生在大一或大二学年申请转入本校其他专业的正式程序，依据教育部《普通高等学校学生管理规定》（教育部令第 41 号）第六十一条与各校转专业管理办法。申请书是转专业考核的重要材料之一，正文约 10001500 字，侧重"为什么转 + 转入后做什么"。多数学校转专业申请窗口集中在大一第二学期末（56 月）或大二第一学期初（9~10 月），错过则等下一年度。
输出文件：可提交的 .docx（A4 纸张，黑体二号标题居中、宋体小四正文、1.5 倍行距、首行缩进 2 字符、"此致/敬礼！"格式、落款右对齐、目标专业课程表与转后学习计划表自动嵌入）。
§0 适用场景与定位
0.1 适用范围
适用：用户提到"转专业""转专业申请书""转系""转院""专业调整""申请转专业""转入XX专业""大一转专业""大二转专业""本科转专业""换专业"等关键词，且本人为大一或大二在校生（少数学校允许大三上学期申请）。
典型场景：
- 大一第二学期末（5~6 月）申请转入其他专业（最常见的窗口期）
- 大二第一学期初（9~10 月）申请转入其他专业（部分学校第二窗口）
- 入学后因身体原因、家庭变故等申请调整专业（特殊通道，需医疗证明或户籍证明）
- 大类培养分流前申请转入其他大类（部分 985 高校大类培养模式）
0.2 不适用场景（需走其他 skill）
- 保研推免：跨专业保研走
graduate_recommendationskill（保研是研究生阶段跨专业，转专业是本科阶段校内转） - 休学复学：复学申请不属于本 skill，需走教务系统提交复学申请表
- 跨校转学：跨校转学走教育部跨校转学流程，非本 skill 范围
- 研究生转导师/转方向：研究生阶段不适用本 skill
- 专科升本科：专升本属于升学考试，非本 skill 范围
- 大类培养分流：大类分流走学校分流系统，但若分流前申请转入其他大类则适用本 skill
0.3 转专业 vs 保研推免 跨专业 关系
转专业与保研推免跨专业是两种不同的"换专业"路径，必须区分清楚：
| 对比项 | 转专业（本 skill） | 保研推免跨专业（graduate_recommendation） |
|---|---|---|
| 申请阶段 | 本科阶段（大一/大二） | 本科毕业前（大三下/大四上） |
| 申请结果 | 本校其他专业本科生 | 外校或本校研究生 |
| 学历层次 | 本科 | 研究生（硕士/直博） |
| 评审材料 | 转专业申请书 + 成绩单 + 笔试面试 | 推免申请表 + 个人陈述 + 推荐信 |
| 字数 | 1000~1500 字 | 1500~2000 字 |
触发后第一步：核对申请阶段。若用户说"我要转专业"且为大一大二在校生 → 本 skill；若用户说"我要跨专业保研"且为大三 → graduate_recommendation skill。若用户混淆（如大三学生说"转专业"），必须追问"您是要本科阶段校内转专业（大一/大二窗口），还是要跨专业保研（研究生阶段）？两者申请阶段与材料差异很大"。
0.4 申请窗口与时间节点
- 大一第二学期窗口（最常见）：5 月初启动 → 5 月中旬提交申请书 → 5 月底笔试 → 6 月初面试 → 6 月中公示 → 9 月新学期入学新专业
- 大二第一学期窗口（部分学校）：9 月初启动 → 9 月中旬提交申请书 → 9 月底考核 → 10 月初公示 → 10 月中转入新专业
- 特殊通道窗口：身体原因/家庭变故随时申请，需医疗证明或户籍证明 + 学校审批
- 申报窗口期：约 2~3 周，错过则等下一年度或下个窗口
- 同年度限制：一般同年度仅可申请 1 个目标专业，部分学校允许 2 个志愿
§1 转专业 3 类对照表（必加章节 1）
1.1 3 类对照表
| 维度 | 兴趣驱动型 | 学业优势型 | 职业规划型 |
|---|---|---|---|
| 核心动机 | 对目标专业有持续兴趣与初步探索 | 在目标专业相关课程/竞赛中表现突出 | 目标专业与长期职业规划高度匹配 |
| 评审侧重 | 兴趣的真实性 + 持续性 + 已有探索 | 学业能力的可迁移性 + 已有成果 | 职业目标的清晰度 + 专业的支撑性 |
| 适用人群 | 高考填报失误 + 入学后自主探索 + 兴趣明显转向 | 现专业某门课与目标专业交叉且高分 + 自学目标专业课程 | 有明确职业方向（如医生/律师/科研）+ 现专业无法支撑 |
| 必备佐证 | 自学笔记/项目/读书清单/相关社团经历 | 高分交叉课程/目标专业相关竞赛/科研经历 | 职业调研报告/实习经历/行业人物访谈 |
| 字数侧重 | 转专业原因段（约 400 字）+ 目标专业认知段（约 400 字） | 现专业学习段（约 350 字）+ 转专业原因段（约 350 字） | 转专业原因段（约 400 字）+ 转后规划段（约 350 字） |
| 常见雷区 | 兴趣无据可查（仅一句"我喜欢"）；贬低现专业 | 学业成绩无量化（仅"成绩优异"）；交叉课程名模糊 | 职业规划空泛（仅"想做XX"）；无行业调研 |
| 评审风险 | 中（需充分佐证兴趣真实性） | 低（学业数据客观可信） | 高（需职业规划具体可执行） |
| 推荐档位 | 1000 字标准版 | 800 字短版（数据为主） | 1500 字长版（规划要详） |
What ships with it
1 file 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.
- 9d ago First seen · 1,301 lines · 195 tokens per session scan A 7d7442b63380
major_transfer is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 195 tokens to every session and 23,457 once invoked, about $0.0010 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 2026-08-31.
Other skills, from other repositories
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
read
Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask in any language to read, fetch, check, summarize, quote, cite, convert, or save a URL or PDF. Not for local…
overleaf-sync
A two-way connection between a local paper folder and Overleaf, a web-based LaTeX editor for writing research papers. It lets you move changes between the local files and the shared Overleaf project.
pdf-verification-cli
Verify PDF page count and content using command-line tools when Python libraries unavailable.