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 agentmods add skills/binary-husky/alphaautoresearch/rednote_covernpx skills add binary-husky/AlphaAutoResearch --skill rednote_covergit clone --depth 1 https://github.com/binary-husky/AlphaAutoResearchWhat 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 | $0.00022 | $0.00867 |
| Opus 5 | $0.00011 | $0.00434 |
| Sonnet 5 | $0.00004 | $0.00173 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
rednote-cover 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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小红书封面图生成详细指南
封面图比例（3:4）竖屏
生成流程
- 查看以下参考图片，转化成html格式。如果有背景，则暂时使用纯色背景
参考图片：https://serve.gptacademic.cn/publish/auto/rednote/图片3.png
html输出路径：./rednote_cover_html_and_sceenshot/main.html
-
使用playwright-cli截图，playwright-cli 需要使用 tmux 运行 （如果你不使用tmux，会遇到GPU错误、网络错误等各种错误），放置到路径：
./rednote_cover_html_and_sceenshot/main.v1.png -
对比 参考图片 和 playwright截图，修改 html 弥合二者的差距，生成 main.v2.png，重复该步骤，生成 main.v3.png、main.v4.png， 直到不再有除了背景图像以外的其他区别，尤其是：
- 界面布局的区别
- 元素位置的区别
- 字体的区别
- 如果图片右下角有皇冠图案水印，移除它
-
使用nano-banana生成与当前文章主题相关的背景图像，色调图参考图片需要基本一致
-
将生成的图像应用到 html 中，最后生成 main.final.png
nano-banana 生成图像的方法
见skill alpha_auto_research/skills/banana_image/SKILL.md
playwright-cli 截图指南
重要：必须在 tmux 中运行
playwright-cli 必须在 tmux 会话中启动浏览器，否则会遇到 GPU 错误、网络错误等问题。
步骤
- 启动 HTTP 服务器（file:// 协议被阻止）：
cd ./rednote_cover_html_and_sceenshot && python3 -m http.server 18888 &
- 在 tmux 中打开浏览器：
tmux new-session -d -s pw "playwright-cli open 'http://localhost:18888/main.html' && sleep 999999"
- 等待浏览器启动后，导航并截图：
# 检查浏览器是否就绪
playwright-cli list
# 导航到页面（如果需要）
playwright-cli goto "http://localhost:18888/main.html"
# 设置视口大小（3:4 比例，如 900x1200）
playwright-cli resize 900 1200
# 截图
playwright-cli screenshot --filename="./rednote_cover_html_and_sceenshot/main.v1.png"
- 迭代修改时，重新加载页面并截图：
playwright-cli reload && playwright-cli screenshot --filename="./rednote_cover_html_and_sceenshot/main.v2.png"
常用命令
| 命令 | 说明 |
|---|---|
playwright-cli list |
列出所有浏览器会话 |
playwright-cli open <url> |
打开浏览器并导航到 URL |
playwright-cli goto <url> |
导航到 URL |
playwright-cli resize <w> <h> |
设置视口大小 |
playwright-cli reload |
重新加载页面 |
playwright-cli screenshot --filename=<path> |
截图保存到指定路径 |
playwright-cli -s=<session> <cmd> |
指定会话执行命令 |
注意事项
- 如果遇到 "browser not open" 错误，检查 tmux 会话是否正常运行
- 截图前确保 HTTP 服务器在运行
- 完成后记得关闭 HTTP 服务器：
pkill -f "python3 -m http.server 18888"
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.
- 2d ago First seen · 102 lines · 22 tokens per session scan A 5c95a75fcce4
rednote-cover is a skill published in the GitHub repository binary-husky/AlphaAutoResearch (11 stars, last pushed 3mo ago), licensed MIT. It adds 22 tokens to every session and 867 once invoked, about $0.0001 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 2026-08-30.
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