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 YiShu5/claude-skills --skill fangpian-course-deckgit clone --depth 1 https://github.com/YiShu5/claude-skillsWrote 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/yishu5/claude-skills/fangpian-course-deck)<a href="https://agentmods.dev/skills/yishu5/claude-skills/fangpian-course-deck"><img src="https://agentmods.dev/badge/skills/yishu5/claude-skills/fangpian-course-deck/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/yishu5/claude-skills/fangpian-course-deck"><img src="https://agentmods.dev/badge/skills/yishu5/claude-skills/fangpian-course-deck.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 | $0.00198 | $0.01916 |
| Opus 5.5 | $0.00079 | $0.00766 |
| Sonnet 5.5 | $0.00040 | $0.00383 |
| Haiku 4.5 | $0.00020 | $0.00192 |
Grade A, and why
fangpian-course-deck 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 yesterday.
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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
方片培训课件模板（fangpian-course-deck）
把任何主题做成统一品牌、小白友好、拿来即用的方片培训课件。源自《方片 AI 小白实战课》（14 页，奶油底 + 方片黄 + 小老虎老师）。
先做三件事
- 确认主题与受众：课程名、面向谁（默认"零基础小白"）、要教会的几件事（建议 3–4 个）、每个方法是否有真实截图/案例。
- 套用品牌：颜色、logo、字体、IP 严格按本技能；更细的品牌规范（更多 logo 变体、色卡、字体安装包、海报模板）读
fangpian-brand-kit技能。 - 按"页面蓝图"搭页：不要自由发挥版式，从 14 页蓝图里挑、按 8 个模块拼。
设计基因（硬规则，不要改）
- 画布 16:9（飞书 Slides 960×540；PPT 13.33×7.5in / 1280×720）。
- 底色：奶油底
#FFFCF2（全部页统一，不用纯白）。 - 主色：方片黄
#FFF300（强调、编号、标签、金句条文字）。 - 墨色：暖黑
#1A1A1A（标题、方块、全宽金句条底）；正文用暖灰#5A564A、辅助灰#787464。 - IP 衬底：浅黄方块
#FFF0B4（放在小老虎背后）；卡片底用白#FFFFFF。 - 字体：中文 Noto Sans SC / 思源黑体（标题 Bold、正文 Regular）；亲和标签可用圆体（江城圆体 / ChillReunion）；英文数字用 Nunito。
- 每个内页都有统一页头：黄色小栏目标签 + 黑色大标题（短句、口语）+ 可选灰色副标题。
- 老虎是"老师"，不是装饰：每页右侧或信息图角落固定一只按场景选的老虎，姿势对照表见下。
8 个可复用模块（拼版只用这些）
- 统一页头框：黄小标签 + 黑色大标题 + 灰副标题。
- 黄色胶囊：眉标/栏目名/标签（圆角矩形，黄底黑字）。
- 黑方块编号：黑底方片黄数字（01–04），用于"学会几件事"和总结。
- 黄方块编号：黄底暖黑数字（1–5），用于步骤流。
- 黑色全宽金句条：圆角黑条 + 居中黄字，给每页一句可记忆结论。
- 白描边卡片：白底 + 暖黑描边圆角卡，装勾选清单或"痛点/解法"对比。
- 浅黄底 IP 方块：右侧固定
#FFF0B4方块 + 一只透明老虎。 - 整幅品牌信息图：复杂知识点做成一张统一风格的 PNG 卡片（黄色页眉胶囊 + 编号蓝/黄模块 + 教师虎 + 方片 logo）整幅嵌入，参考
assets/infographics/。
小老虎角色对照（从 assets/tigers 选，按情绪不按喜好）
| 姿势文件 | 用在 | 场景 |
|---|---|---|
01-pointing-cover.png |
封面 / 收尾金句 | 招手、欢迎、指引 |
02-teacher.png |
概念讲解、信息图角落 | 戴眼镜拿教鞭，"老师" |
03-suit-doc.png |
实战演示、文档操作 | 西装拿文件，办公场景 |
04-robot-ai.png |
AI / Skill / 自动化 | 机甲抱 AI 面板 |
05-phone-tool.png |
工具、数据爬取、App | 拿手机 |
06-team-scroll.png |
团队协作、信息源 | 双人卷轴 |
07-trophy.png |
总结回顾、成果 | 举奖杯 |
08-thumb-action.png |
行动清单、号召 | 戴红头巾点赞 |
标准 14 页节奏（可按主题增减，顺序不变）
封面 → 课程地图（学会 4 件事）→ 核心认知（1 个比喻/纠偏）→ 每个方法（是什么→为什么→现场演示→好习惯，每方法 2–3 页）→ 总结回顾（4 件事）→ 行动清单（回去先做 3 件事）→ 金句收尾。
逐页模块组合、版式比例和示例文案见 references/page-blueprints.md。
制作流程（落到飞书 Slides / PPT）
- 先定课程骨架：课程名 + 一句 slogan + 学会的 N 件事 + 每个方法的演示案例与截图。
- 复杂知识点先产出整幅信息图（仿
assets/infographics/的卡片样式：黄胶囊页眉、编号模块、教师虎、logo）；操作类内容直接截真实软件界面图。 - 用飞书 slides 技能逐页搭：页头/清单/卡片用原生可编辑形状（便于改），信息图与老虎用透明 PNG（老虎不要白底，用
assets/tigers/已抠图）。 - 每一页落一句金句（黑条黄字）；封面和收尾各一只招手虎，行动页用点赞虎。
- 自检：每页有页头、右侧或角落有虎、颜色只用规定色板、正文不堆字、截图能看清、结论口语化。
What ships with it
18 files 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.
- assets/infographics/01-five-parts.png 1221 KB
- assets/infographics/02-one-task-one-chat.png 1467 KB
- assets/infographics/03-choose-model.png 1593 KB
- assets/infographics/04-skill-compare.png 115 KB
- assets/infographics/05-skill-find.png 170 KB
- assets/logos/logo-black.png 191 KB
- assets/logos/logo-white.png 139 KB
- assets/tigers/01-pointing-cover.png 581 KB
- assets/tigers/02-teacher.png 761 KB
- assets/tigers/03-suit-doc.png 674 KB
- assets/tigers/04-robot-ai.png 983 KB
- assets/tigers/05-phone-tool.png 753 KB
- assets/tigers/06-team-scroll.png 880 KB
- assets/tigers/07-trophy.png 910 KB
- assets/tigers/08-thumb-action.png 826 KB
- references/content-method.md 4.3 KB
- references/design-system.md 4.6 KB
- references/page-blueprints.md 7.0 KB
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.
- yesterday First seen · 81 lines · 198 tokens per session scan A e59f9eb47800
fangpian-course-deck is a skill published in the GitHub repository YiShu5/claude-skills (132 stars, last pushed yesterday), licensed MIT. It adds 198 tokens to every session and 1,916 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-10-17.
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