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 tech_servicegit 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-/tech_service)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/tech_service"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/tech_service/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-/tech_service"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/tech_service.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 | $0.00110 | $0.19628 |
| Opus 5 | $0.00055 | $0.09814 |
| Sonnet 5 | $0.00022 | $0.03926 |
| Haiku 4.5 | $0.00011 | $0.01963 |
Grade A, and why
tech_service 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 — 966 lines — stays where its author put it; the contents beside it link to each section on GitHub.
三下乡社会实践-科技服务类 Skill
本 skill 处理"大学生暑期三下乡社会实践-科技服务类"立项申报书全流程：信息采集 → 服务需求分析 → 专业能力匹配 → 服务方案设计 → 按场次实施 → docx 生成 → 质检。仅处理"科技服务类"子类（科技/医疗/法律/农业技术服务为主），调研/支教/宣讲类请走对应 skill。
科技服务类与调研/支教/宣讲类的核心区别在于"专业输出"——评审看的是服务专业性、需求匹配度、可持续性，而非数据采集（调研）、教学方法（支教）或一对多传达（宣讲）。科技服务类申报书必须有：服务对象需求清单 + 专业能力匹配矩阵 + 按服务场次实施方案 + 服务人次与解决方案量化产出 + 持续帮扶机制。
输出文件：可提交的 .docx（A4 纸张，宋体小四正文，黑体三号标题，1.5 倍行距，首行缩进 2 字符）。
一、适用场景与触发条件
适用：用户提到"三下乡""社会实践""科技服务""医疗服务""法律援助""农业技术指导""IT 维修""电商培训""数字素养培训""上门服务""暑期社会实践立项申报书"等关键词，且实践主要形式为面向村民/社区居民提供专业技术服务（非走访调研、非中小学支教、非集中宣讲）。
不适用（需走其他 skill）：
- 调研类（含问卷 + 访谈，调研报告为核心产出）→ 走 social_survey skill
- 支教类（含课时安排、教学对象为中小学生、有教案）→ 走 volunteer_teaching skill
- 宣讲类（含宣讲场次、一对多集中传达、宣讲大纲）→ 走 policy_lecture skill
- 单纯志愿服务（无专业技术服务输出，如敬老陪伴）→ 走志愿服务 skill
四种服务子方向速查：
| 子方向 | 典型选题 | 专业背景要求 | 服务对象 |
|---|---|---|---|
| 科技服务 | IT 维修、电商培训、数字素养、智能手机使用 | 计算机/通信/电子/电子商务 | 村民、村电商、留守老人 |
| 医疗服务 | 健康体检、慢病管理、急救培训、中医药科普 | 临床医学/护理/药学/公共卫生 | 村民、老年人、慢病患者 |
| 法律援助 | 民法典宣讲与咨询、反诈、未成年人保护、土地纠纷 | 法学/知识产权 | 村民、妇女、外出务工人员 |
| 农业技术指导 | 种植技术、养殖防疫、农机使用、农产品加工 | 农学/园艺/植物保护/动物科学 | 种养殖大户、合作社、家庭农场 |
触发条件组合：用户输入包含"三下乡/社会实践" + "科技服务/医疗服务/法律援助/农业技术指导/IT 维修/电商培训/数字素养"中任一 → 进入本 skill。
默认假设：未明确说明时默认为科技服务子方向（覆盖最广、立项通过率最高、与高校学科匹配度最高）。用户若指向其他三类，按对应子方向调整服务内容与专业要求。
科技服务类 vs 其他子类核心区别：
- 科技服务类：核心产出是"服务人次 + 解决方案 + 持续帮扶机制"，强调专业输出
- 调研类：核心产出是"调研报告"，强调数据收集与分析
- 支教类：核心产出是"支教课时 + 学生反馈"，强调教学方法
- 宣讲类：核心产出是"宣讲场次 + 受众覆盖"，强调内容传达
二、工作流程总览
1. 子方向确认
→ 确认服务子方向（科技/医疗/法律/农业）→ 锁定服务对象类型
→ 明确团队专业能力是否匹配（必须有对应学科背景成员）
2. 信息采集
→ 通用 10 字段 + 服务专属 12 字段（详见第三章）
→ 分批追问，不替用户编造服务能力
3. 服务需求分析
→ 调研服务对象实际需求 → 列出需求清单 → 按优先级排序 → 匹配团队专业能力
4. 专业能力匹配
→ 团队成员专业背景 → 服务内容 → 匹配度评估（高/中/低）
→ 低匹配项必须由指导教师补充或调整服务内容
5. 服务方案设计
→ 每项需求对应 1 套解决方案（服务流程 + 工具 + 预期解决程度）
→ 总服务场次 5~8 场，覆盖 150~300 人次
6. 按场次实施安排
→ 每场：场次序号 + 日期 + 地点 + 服务对象 + 服务内容 + 人数 + 专业要求
→ 5~8 行覆盖整个实践期
7. 持续帮扶机制
→ 建立"线上 + 线下"长效服务，每月 1 次远程答疑，每季度 1 次现场回访
8. docx 生成
→ python build.py --data data.json --out output.docx
9. 质检
→ 专业匹配度 + 需求匹配度 + 场次人数加总 + 持续机制可行性
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 · 966 lines · 110 tokens per session scan A 585f775367d1
tech_service is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 110 tokens to every session and 19,628 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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