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 outstanding_graduategit 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-/outstanding_graduate)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/outstanding_graduate"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/outstanding_graduate/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-/outstanding_graduate"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/outstanding_graduate.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 | $0.00142 | $0.14423 |
| Opus 5 | $0.00071 | $0.07211 |
| Sonnet 5 | $0.00028 | $0.02885 |
| Haiku 4.5 | $0.00014 | $0.01442 |
Grade A, and why
outstanding_graduate 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.
优秀毕业生申请书 Skill
本 skill 处理"优秀毕业生申请书"全流程：信息采集 → 4 年成长叙事撰写 → docx 生成 → 质检。优秀毕业生是本科生毕业前最高规格的综合荣誉，评审跨度为大学 4 年（与"优秀学生"一学年跨度不同），要求总结 4 年综合表现与毕业去向。支持省级与校级两种规格。
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、4 年 GPA 表与科研竞赛成果表自动嵌入）。
一、适用场景与触发条件
适用：用户提到"优秀毕业生""省优毕业生""校优毕业生""省级优秀毕业生""校级优秀毕业生""毕业生评优"等关键词，且本人应届毕业（大四下学期）。
不适用（需走其他 skill）：
- 优秀学生 / 优秀团员 / 文明大学生（一学年跨度，1500~2000 字）→ 走评优其他 skill
- 国家奖学金（一学年跨度，1200~2000 字，侧重本学年表现）→ 走 national_scholarship
- 保研推免申请书（侧重研究生申请，含推荐信）→ 走推免相关 skill
省校规格区分：
- 省级：规格高，配额 3%~5%，需校级优秀毕业生资格 + 学校择优推荐
- 校级：常规规格，配额 5%~10%，学院初审 + 学校终审
- 同一学生同年度可同时申报省校两级，但申请书须分别按规格调整数据展示
硬门槛（任一不达标直接劝退）：
- 大学 4 年加权 GPA ≥85 或 GPA 3.5+/4.0
- 4 年内无挂科、无违纪处分
- 已通过毕业论文/设计开题，且进入中期以上阶段
- 至少 2 项校级及以上荣誉（含奖学金、竞赛、三好学生等）
- 毕业去向明确（升学/就业/创业/西部计划/选调/留学，须有录取或签约证明）
触发后第一步：核对硬门槛与申报规格。若用户 GPA 不达 4 年综合门槛或无 2 项校级荣誉，告知"优秀毕业生评审侧重 4 年综合表现与毕业去向，建议补足荣誉后再申"。区分省校规格，省校分别出具。
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（10~15 轮对话）： 按"通用必采 → 4 年学业信息 → 思想品德 → 科研创新 → 社会实践 → 综合素质 → 毕业去向"顺序采集。每轮不超过 5 个字段。关键缺失字段必须追问，禁止编造 GPA/排名/竞赛/论文/志愿服务时长/毕业去向。
阶段 2 4 年成长叙事撰写（一次性产出）： 按"标题 → 称呼 → 开头 → 思想品德 → 学业成绩 → 科研创新 → 社会实践 → 综合素质 → 结尾 → 落款"顺序撰写。正文 2000~3000 字，每段严格控制在规范区间。必须体现 4 年成长轨迹（不是简单罗列事项）。
阶段 3 docx 生成：
调用 python build.py --data data.json --out output.docx 生成 Word 文档。data.json 字段定义见第十二章。
阶段 4 质检： 按第十三章 30 项清单逐项检查。任何一项不达标返回阶段 2 修改。
禁止行为：
- 开头抒情堆砌（"时光荏苒""岁月如梭""四年光阴转瞬即逝"）
- 形容词代替事实（"成绩优异""积极参加""全面发展"）
- 获奖不写级别与时间
- 学生干部只写头衔不写履职
- 4 年成长叙事变成按时间流水账
- 毕业去向一笔带过（"已保研至清华大学"）
- 结尾"恳请领导批准"
- 编造 GPA/排名/竞赛/论文/志愿服务时长/毕业去向
三、信息采集清单
3.1 通用必采（12 字段）
| 字段 | 说明 | 示例 | 缺失追问策略 |
|---|---|---|---|
| name | 申请人姓名 | 张明 | "申请人全名？" |
| student_id | 学号 | 2021123456 | "学号？" |
| gender | 性别 | 男 | "性别？" |
| college | 学院全称 | 计算机科学与技术学院 | "学院全称？" |
| major | 专业全称 | 计算机科学与技术 | "专业全称？" |
| grade | 年级 | 2021 级 大四 | "入学年份？" |
| class_name | 班级 | 计科 2101 班 | "班级？" |
| political_status | 政治面貌 | 中共党员 | "政治面貌？" |
| phone | 联系电话 | 138XXXXXXXX | "手机号？" |
| apply_level | 申报规格 | provincial / school | "省级还是校级？" |
| apply_year | 毕业年份 | 2025 届 | "毕业年份？" |
| apply_date | 申报日期 | 2025 年 5 月 20 日 | "申报日期？" |
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 · 142 tokens per session scan A a2ed86833573
outstanding_graduate is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 142 tokens to every session and 14,423 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 2026-08-31.
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