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 policy_lecturegit 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-/policy_lecture)<a href="https://agentmods.dev/skills/cuic19053-hue/-skills-/policy_lecture"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/policy_lecture/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-/policy_lecture"><img src="https://agentmods.dev/badge/skills/cuic19053-hue/-skills-/policy_lecture.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 | $0.00121 | $0.17188 |
| Opus 5 | $0.00060 | $0.08594 |
| Sonnet 5 | $0.00024 | $0.03438 |
| Haiku 4.5 | $0.00012 | $0.01719 |
Grade A, and why
policy_lecture 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.
三下乡社会实践-宣讲类 Skill
本 skill 处理"大学生暑期三下乡社会实践-宣讲类"立项申报书全流程：信息采集 → 宣讲主题选定 → 宣讲大纲设计 → 对象分析 → 按场次方案撰写 → docx 生成 → 质检。仅处理"宣讲类"子类（政策/党史/普法/科技宣讲为主），支教/调研/科技服务类请走对应 skill。
宣讲类与调研/支教/服务类的核心区别在于"内容输出"——评审看的是宣讲内容的政治性、针对性、通俗化表达，而非教学方法（支教）或数据采集（调研）。宣讲类申报书必须有：明确宣讲主题 + 宣讲大纲 + 按场次实施方案 + 覆盖人次量化产出。
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""宣讲类""政策宣讲""党史宣讲""普法宣讲""科技宣讲""党的二十大精神宣讲""乡村振兴促进法宣讲""民法典宣讲""数字素养宣讲""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/社区居民开展集中宣讲（非支教、非走访调研、非技术维修服务）。
不适用（需走其他 skill）：
- 支教类（含课时安排、教学对象为中小学生、有教案）→ 走支教 skill
- 调研类（含问卷发放、深度访谈、调研报告产出）→ 走调研 skill
- 科技服务类（含技术培训 + 设备维修/上门服务）→ 走服务 skill
- 单纯志愿服务（无宣讲内容输出）→ 走志愿服务 skill
触发后第一步：确认实践形式为"宣讲类"（含宣讲主题 + 宣讲场次 + 宣讲材料印制）。若用户未明确主题，按四类宣讲主题（政策/党史/普法/科技）逐一询问确定。
四种宣讲主题速查：
| 主题类型 | 典型选题 | 政策依据 | 宣讲对象 |
|---|---|---|---|
| 政策宣讲 | 党的二十大精神、二十届三中全会精神、中央一号文件 | 团中央年度主题、中共中央文件 | 村干部、党员、村民代表 |
| 党史宣讲 | 党的百年奋斗史、地方党史、红色故事、英雄事迹 | 党史学习教育常态化要求 | 党员、青少年、村民 |
| 普法宣讲 | 民法典、乡村振兴促进法、反诈、未成年人保护法 | 八五普法规划、司法部年度普法要点 | 村民、妇女、青少年 |
| 科技宣讲 | 数字素养、农业技术、健康科普、防灾减灾 | 全民科学素质行动规划纲要 | 普通村民、种养殖大户 |
触发条件组合：用户输入包含"三下乡/社会实践" + "宣讲/宣讲类/政策宣讲/党史宣讲/普法宣讲/科技宣讲"中任一 → 进入本 skill。
默认假设：未明确说明时默认为政策宣讲类（覆盖最广、立项通过率最高）。用户若指向其他三类，按对应主题调整宣讲大纲与材料清单。
二、工作流程总览
1. 主题确认
→ 确认宣讲类型（政策/党史/普法/科技）→ 锁定主题（如"党的二十大精神"）
→ 明确政策依据与对象画像
2. 信息采集
→ 通用 10 字段 + 宣讲专属 12 字段（详见第三章）
→ 分批追问，不替用户编造
3. 宣讲大纲设计
→ 开场 5 分钟 + 主体 3 点（每点 15 分钟）+ 案例 10 分钟 + 互动 10 分钟 + 结尾 5 分钟
→ 每点配 1 个通俗化表达 + 1 个本地案例
4. 对象分析
→ 年龄结构 / 文化程度 / 关注点 / 接受方式
5. 按场次方案撰写
→ 每场：日期 + 地点 + 对象 + 人数 + 时长 + 主讲人
→ 3~5 场为佳，单场覆盖 30~80 人，总覆盖 150~400 人次
6. 材料清单与印制
→ 宣讲手册、宣传单页、易拉宝、互动小礼品
7. docx 生成
→ python build.py --data data.json --out output.docx
8. 质检
→ 政治用语规范 + 通俗化检查 + 场次人数加总
关键节点控制：
- 主题确认阶段不锁定主题前不进入大纲设计，避免后期返工
- 大纲设计必须先讲通"通俗化"再讲"准确性"——村民听不懂的宣讲是失败的
- 按场次表必须按"日"为粒度列出（不能用"前期/中期/后期"）
- 预期成果必须以"场次 + 覆盖人次 + 材料印制"为主，不能只写"扩大影响"
与调研/支教/服务的边界判定：宣讲类有"一对多集中传达"特征；调研类有"问卷+访谈"特征；支教类有"中小学生+课时"特征；服务类有"上门+维修/培训"特征。混合实践以主要形式归类。
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 · 121 tokens per session scan A 4b8a876831b8
policy_lecture is a skill published in the GitHub repository cuic19053-hue/-skills- (10 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 17,188 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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