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 cuic19053-hue/-skills- --skill university_scholarshipgit clone --depth 1 https://github.com/cuic19053-hue/-skills-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-/university_scholarship)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/university_scholarship"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/university_scholarship/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-/university_scholarship"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/university_scholarship.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 | $0.00123 | $0.13097 |
| Opus 5 | $0.00062 | $0.06549 |
| Sonnet 5 | $0.00025 | $0.02619 |
| Haiku 4.5 | $0.00012 | $0.01310 |
Grade A, and why
university_scholarship 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 12d 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 — 966 lines — stays where its author put it; the contents beside it link to each section on GitHub.
校级奖学金申请书 Skill
本 skill 处理"校级奖学金申请书"全流程：信息采集 → 等级匹配 → 书信体撰写 → docx 生成 → 质检。校级奖学金是本科生最易申请的奖学金（门槛最低、覆盖面最广），评审侧重纯学习：GPA、专业排名、单科成绩；不强制要求科研、竞赛、志愿服务。仅处理校级一/二/三等，国家奖学金（8000 元）与国家励志奖学金（5000 元）请走其他 skill。
子类型与硬门槛：
- 校级一等：GPA 加权平均分 ≥85，专业排名前 5%（如 4/87）
- 校级二等：GPA 加权平均分 ≥80，专业排名前 15%（如 10/87）
- 校级三等：GPA 加权平均分 ≥75，专业排名前 30%（如 20/87）
与国奖的关键区别：弱化科研实践（不强制要求）、强化纯学业表现（学业权重 70%）、申请书更短（8001500 字而非 12002000 字）、不强制国家级竞赛或论文。
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）。
一、适用场景与触发条件
适用：用户提到"校级奖学金""校奖学金""校一等/二等/三等奖学金""大学奖学金""学校奖学金"等关键词，且本人 GPA 排名专业前 30%。等级由用户学业数据自动判定（亦可由用户指定）。
不适用（需走其他 skill）：
- 国家奖学金（8000 元，需国家级竞赛/论文，GPA 前 5%）→ 走国奖 skill
- 国家励志奖学金（5000 元，需家庭经济困难认定）→ 走励志 skill
- 企业专项奖学金（侧重行业兴趣与职业规划）→ 走企业奖学金 skill
- 单项奖学金（科研/社工/文体，仅看单项突出）→ 走单项奖学金 skill
等级判定规则（按数据自动匹配，用户也可手动指定）：
| 等级 | 加权平均分门槛 | 专业排名门槛 | 金额参考 | 覆盖面 |
|---|---|---|---|---|
| 校级一等 | ≥85 | 前 5% | 1500~3000 元 | 3%~5% |
| 校级二等 | ≥80 | 前 15% | 1000~1500 元 | 8%~10% |
| 校级三等 | ≥75 | 前 30% | 500~800 元 | 15%~20% |
子类型区分：
- 校级 vs 国奖：校级仅需 GPA，国奖需国家级竞赛/论文，GPA 前 5%
- 校级 vs 励志：校级不写家庭困难，励志必须含家庭经济情况段
- 校级一等 vs 二等 vs 三等：硬门槛与字数侧重不同（详见第七章）
触发后第一步：核对硬门槛。若用户排名 >30% 或加权 <75，告知"校级奖学金最低门槛为加权 75 + 排名前 30%，建议改申企业专项或单项奖学金"，避免无效申请。等级优先按用户指定，否则按学业数据自动匹配。
二、工作流程总览
四阶段串行执行，每阶段完成后再进入下一阶段：
阶段 1 信息采集（5~8 轮对话）： 按"通用必采 → 学业信息（重点） → 学期 GPA 表 → 荣誉经历 → 科研实践（可选） → 生活方面"顺序采集。每轮不超过 5 个字段。校级奖学金学业信息是核心，必须采集完整。科研实践与志愿服务为可选项，缺则跳过对应段落。
阶段 2 等级匹配与书信体撰写（一次性产出）： 先按学业数据匹配等级（或采用用户指定等级），再按"标题 → 称呼 → 开头 → 思想方面 → 学习方面（重点，占 50% 篇幅） → 科研实践方面（可选） → 生活方面 → 结尾 → 落款"顺序撰写。正文 800~1500 字，每段严格控制在规范区间。事实+数据原则，禁止形容词堆砌。
阶段 3 docx 生成：
调用 python build.py --data data.json --out output.docx 生成 Word 文档。data.json 字段定义见第十一章，需包含 level 字段（一等/二等/三等）、core_courses 主干课程列表、semester_gpa 学期 GPA 表（4 学期）。
阶段 4 质检： 按第十二章 25 项清单逐项检查。任何一项不达标返回阶段 2 修改。重点检查等级与数据是否匹配、主干课程表与学期 GPA 表是否齐全。
禁止行为：
- 开头抒情堆砌（"时光荏苒""岁月如梭"）
- 形容词代替事实（"成绩优异""积极参加"）
- 获奖不写级别与时间
- 学生干部只写头衔不写履职
- 结尾"恳请领导批准"
- 编造 GPA/排名/单科成绩
- 把国奖内容（国家级竞赛/论文）作为主体段
- 把励志内容（家庭困难）写入校级申请书
- 等级与学业数据不匹配（如三等数据却申请一等）
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.
- 12d ago First seen · 966 lines · 123 tokens per session scan A 7f327095112a
university_scholarship is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 123 tokens to every session and 13,097 once invoked, about $0.0006 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.
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