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 enterprise_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-/enterprise_scholarship)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/enterprise_scholarship"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/enterprise_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-/enterprise_scholarship"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/enterprise_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 | $0.00116 | $0.14323 |
| Opus 5 | $0.00058 | $0.07161 |
| Sonnet 5 | $0.00023 | $0.02865 |
| Haiku 4.5 | $0.00012 | $0.01432 |
Grade A, and why
enterprise_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 11d 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.
企业专项奖学金申请书 Skill
本 skill 处理"企业专项奖学金申请书"全流程：信息采集 → 书信体撰写 → docx 生成 → 质检。企业专项奖学金由企业赞助、与特定行业/公司绑定，评审侧重学习+行业兴趣+职业规划，与国奖（侧重学业+综合素质）、励志（侧重学习+家庭经济）有本质区别。仅处理"企业专项"，国家奖学金与校级奖学金请走其他 skill。
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、含三阶段职业规划表）。
一、适用场景与触发条件
适用：用户提到"企业专项奖学金""企业奖学金""华为奖学金""腾讯奖学金""中石化奖学金""字节跳动奖学金""阿里奖学金""百度奖学金""中兴奖学金""国家电网奖学金""行业奖学金""校企合作奖学金"等关键词。
不适用（需走其他 skill）：
- 国家奖学金（8000 元，侧重 GPA 排名+国家级竞赛+论文）→ 走国奖 skill
- 国家励志奖学金（5000 元，侧重学习+家庭经济困难）→ 走励志 skill
- 校级一等奖学金（侧重纯学习 GPA）→ 走校级奖学金 skill
- 单项奖学金（科研/社工/文体）→ 走单项奖学金 skill
常见企业奖学金清单：
- 信息通信类：华为"种子"奖学金、中兴奖学金、中国移动通信奖学金、大唐电信奖学金
- 互联网类：腾讯奖学金、字节跳动奖学金、阿里巴巴奖学金、百度奖学金、美团奖学金、京东奖学金
- 能源化工类：中石化奖学金、中石油奖学金、中海油奖学金、国家电网奖学金、南方电网奖学金
- 金融类：工行奖学金、建行奖学金、招行奖学金、人保财险奖学金
- 制造类：宝钢奖学金、徐工奖学金、三一重工奖学金、海尔奖学金
- 交通建筑类：中建奖学金、中铁奖学金、中交奖学金、顺丰奖学金
硬门槛（任一不达标直接劝退）：
- GPA 加权平均分 ≥80 或 GPA 3.0+/4.0，专业排名前 30%
- 本学年无挂科、无违纪处分
- 申请人专业与企业所属行业有匹配度（如华为奖学金面向电子信息/计算机/通信类，中石化奖学金面向化工/石油/材料类）
- 对该企业所属行业有真实了解（不能套话）
子类型区分：
- 企业专项 vs 国奖：企业专项重行业兴趣+职业规划，国奖重学业+综合素质
- 企业专项 vs 励志：企业专项不要求家庭经济困难
- 企业专项 vs 校级：企业专项必含行业认识与职业规划，校级仅需学业
触发后第一步：核对申请企业与本人专业是否匹配。若用户为文科专业却申请中石化奖学金，告知"该企业奖学金面向化工/能源类相关专业"，建议改申匹配度更高的奖学金。
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（10~14 轮对话）： 按"通用必采 → 学业信息 → 企业专属信息（含企业名/行业地位/认识/职业规划）→ 科研实践 → 生活方面"顺序采集。每轮不超过 5 个字段。关键缺失字段必须追问，禁止编造对企业产品/技术/战略的认识。
阶段 2 书信体撰写（一次性产出）： 按"标题 → 称呼 → 开头 → 思想方面 → 学习方面 → 行业认识【重点】→ 职业规划【重点】→ 科研实践 → 生活方面 → 结尾 → 落款"顺序撰写。正文 1000~1800 字，行业认识与职业规划合计占总字数 40% 以上。
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： 按第十三章质检清单逐项检查。任何一项不达标返回阶段 2 修改。
禁止行为：
- 行业认识套话堆砌（"贵公司是行业领军企业"）
- 职业规划空泛（"希望未来能为公司做贡献"）
- 对企业产品/技术不了解却假装内行
- 申请人专业与企业所属行业完全无关却硬申请
- 开头抒情堆砌、形容词代替事实
- 结尾"恳请领导批准"
- 编造 GPA/排名/实习经历/项目合作经历
三、信息采集清单
3.1 通用必采（10 字段）
| 字段 | 说明 | 示例 | 缺失追问策略 |
|---|---|---|---|
| name | 申请人姓名 | 李伟 | "申请人全名？" |
| student_id | 学号 | 2022112345 | "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 | 2022 级 大三 | "入学年份与年级？" |
| class_name | 班级 | 计科 2202 班 | "班级？" |
| political_status | 政治面貌 | 共青团员 | "政治面貌？" |
| phone | 联系电话 | 138XXXXXXXX | "手机号？" |
| apply_year | 申报学年 | 2024-2025 学年 | "申报学年？" |
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.
- 11d ago First seen · 966 lines · 116 tokens per session scan A 54ffa3ef7673
enterprise_scholarship is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 116 tokens to every session and 14,323 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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