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 sanhuang520-ship-it/awesome-chinese-ai-tools --skill github-readme-cngit clone --depth 1 https://github.com/sanhuang520-ship-it/awesome-chinese-ai-toolsWrote 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/sanhuang520-ship-it/awesome-chinese-ai-tools/github-readme-cn)<a href="https://agentmods.dev/skills/sanhuang520-ship-it/awesome-chinese-ai-tools/github-readme-cn"><img src="https://agentmods.dev/badge/skills/sanhuang520-ship-it/awesome-chinese-ai-tools/github-readme-cn/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/sanhuang520-ship-it/awesome-chinese-ai-tools/github-readme-cn"><img src="https://agentmods.dev/badge/skills/sanhuang520-ship-it/awesome-chinese-ai-tools/github-readme-cn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 133 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00099 | $0.02119 |
| Opus 5.5 | $0.00040 | $0.00848 |
| Sonnet 5.5 | $0.00020 | $0.00424 |
| Haiku 4.5 | $0.00010 | $0.00212 |
Grade A, and why
github-readme-cn 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 1mo 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub 中文项目门面优化
先说清楚这个技能不做什么：它不能让你的项目火。
下面的建议来自对 15 个近期高增长仓库的结构实测。这些是相关性，不是因果—— 我能测到"12/15 首屏有图"，但测不到"因为有图所以火"。真正决定传播的是有没有人替你转发， 而那个变量不在 README 里。
把门面做好的意义是：当流量真的来的时候，不至于漏掉。 仅此而已。
什么时候用
写或重写开源项目的 README、仓库描述、topics；项目做完了没人看想找原因； 准备投稿到社区/周刊之前的自查。
第一步：先问清楚三件事
- 仓库地址（有的话直接看现状，没有就问定位）
- 目标读者是谁——中文开发者？特定行业？海外？决定语言和例子
- 这个项目和同类比，凭什么选它——答不上来的话，README 写得再漂亮也没用
⚠️ 用户说"帮我优化 README"时，不要直接开始写。 先看他现在的 README 和仓库，指出具体差在哪，再动手。凭空写出来的通常是套话。
首屏是唯一重要的位置
GitHub 上不滚动能看到的大约是 README 前 15 行。绝大多数人只看这一屏。
实测：15 个高增长仓库的首屏
| 特征 | 命中 | 说明 |
|---|---|---|
| 首屏有图 | 12/15 | 最普遍的一条 |
| 首屏有徽章 | 11/15 | shields.io |
| 首屏有安装命令 | 4/15 | 少见，但对工具类很有用 |
| 首屏能点到 demo | 3/15 | 少见，做了就是差异化 |
| 标题用中文 | 2/15 | 即便是中文项目也多用英文名 |
中位数参考：README 15 KB · 图片 10 张 · 仓库名 14 字符 · topics 9 个
首屏该有的东西，按顺序
<div align="center">
<img src="真实产品截图或效果图" width="100%">
# 项目名
**一句话说清楚它给你什么**（不是"这是一个基于 XX 的 YY 框架"）
[徽章] [徽章] [徽章]
[🌐 在线体验] · [📋 文档] · [📸 效果图]
</div>
> **和同类比有什么不一样**
> ① …… ② …… ③ ……
```bash
一行就能跑起来的命令
---
## 关于首屏那张图
**用真实产出，不要用设计稿或抽象插画。**
如果你的项目输出是可视的（网页、图表、CLI 界面、渲染结果），
直接 headless 截图，比任何设计稿都有说服力：
```bash
"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
--headless --disable-gpu --hide-scrollbars \
--force-device-scale-factor=2 --window-size=1400,900 \
--screenshot=shot.png "https://你的页面"
多张拼成一条横幅比单张更能体现"有内容"。PNG 转 WebP 通常能省 80%+ 体积。
⚠️ 截图前务必确认它真的反映差异。常见翻车：用 ?theme=xxx 之类的 URL 参数截 8 张"不同主题"，
结果参数根本不生效，8 张图 md5 完全相同。截完对一下哈希。
⚠️ 样张里不要编数据。演示文案里写"测试 200 组样本，准确率 91%"这种， 读起来像真实结果——如果你没测过，这就是造假。
命名与描述
| 项 | 建议 |
|---|---|
| 仓库名 | 中位数 14 字符。awesome-chinese-ai-tools（24）就偏长，且带了已经不准的词 |
| 仓库描述 | GitHub 搜索结果里显示的就是这句。放数字和差异点，别放形容词 |
| topics | 上限 20 个。用目标用户真正会搜的词，不是你觉得贴切的词 |
topics 是最容易被忽略的一环。检查方法：去 GitHub 搜你希望被搜到的词， 看排前面的仓库都打了哪些 topic。如果你的词和他们完全不重合，就是搜不到的原因。
⚠️ 用英文词搜，也打英文 topic。 2026-08-28 实测：
元素周期表的前 5 名 没有一个是周期表项目，互动学习 物理 化学返回 0 结果；换成periodic table interactive则前 5 全部相关。中文项目可以有中文说明， 但别指望中文关键词把人带过来。（数据见references/measured-data.md第四节）
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.
- 1mo ago First seen · 182 lines · 99 tokens per session scan A 5ace90a50ffb
github-readme-cn is a skill published in the GitHub repository sanhuang520-ship-it/awesome-chinese-ai-tools (11 stars, last pushed yesterday), licensed MIT. It adds 99 tokens to every session and 2,119 once invoked, about $0.0004 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 2026-08-31.
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