Agent skill

Huashu Image Upload

by alchaincyf in alchaincyf/huashu-skills

文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。

MITAuto-check passedDocuments & Office

Install Huashu Image Upload

skills CLI
$ npx skills add alchaincyf/huashu-skills --skill huashu-image-upload -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alchaincyf/huashu-skills huashu-image-upload --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alchaincyf/huashu-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/huashu-image-upload .claude/skills/huashu-image-upload && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
huashu-image-upload
GitHub stars
1.7k
Token cost
~989 tokens
SKILL.md length
216 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。

  • Works in 5 steps: 分析文章,确定配图需求 → 获取/生成图片 → 上传到图床,获取永久链接 → …
  • Tasks that involve Markdown
  • SKILL.md covers 何时使用此Skill, 核心功能, 配图数量规范 and 配图位置策略, plus 9 more sections
  • Calls python3; reaches i.ibb.co

What it does

Huashu Image Upload is an agent skill from alchaincyf/huashu-skills. 文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering Markdown. It works with Wikipedia. The repository describes itself as: 花叔全部开源 Agent Skills 总目录:16 旗舰 + 14 人物视角 + 22 内置共 52 个 skill,分层分类 + AI Agent 安装协议 + 机器可读 skills.json + 更新检查机制. The licence is MIT.

When your agent uses it

  • Tasks that involve Markdown

Example prompts

  • “/huashu-image-upload”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 分析文章,确定配图需求
  2. 获取/生成图片
  3. 上传到图床,获取永久链接
  4. 在文章中插入图片
  5. 验证显示

What it can do on your machine

Read from SKILL.md and the folder at commit 2efea35. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • i.ibb.co

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Huashu Image Upload loads about 989 tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 216 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~989

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alchaincyf/huashu-skills at commit 2efea35, republished under its MIT licence (© alchaincyf). 216 words, ~989 tokens.

Download SKILL.mdSave it as .claude/skills/huashu-image-upload/SKILL.md (or your agent's skills folder).
name
huashu-image-upload
description
文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。

图片配图与上传

为公众号文章自动生成配图、上传到图床、插入Markdown链接的专业能力。

何时使用此Skill

当检测到以下场景时,自动加载此skill:

  • 用户说"现在配图"、"帮我配图"、"添加图片"
  • 文章审校完成后提到配图需求
  • 检测到文章内容完整但缺少图片

核心功能

  1. 分析配图需求:根据文章内容确定需要5-8张配图
  2. 获取图片源:
    • 公共领域作品(Wikimedia Commons、Google Arts & Culture)
    • AI生成图片(火山引擎 doubao-seedream API)
    • 免费图库(Unsplash、Pexels)
  3. 自动上传图床:调用ImgBB图床,获取永久链接
  4. 插入Markdown:将图片链接插入文章对应位置
  5. 验证显示:确保所有图片链接有效

配图数量规范

  • 推荐:5-8张
  • 最少:3张(题图 + 2张正文图)
  • 最多:不超过10张(避免过度打断阅读)

配图位置策略

必配图位置:

  • ✅ 题图(封面图):标题下方,必须
  • ✅ 核心章节:每个重点章节配1张

可选配图位置:

  • 理论支撑(如引用经典著作)
  • 数据可视化(对比图、图表)
  • 案例补充(产品截图、示例)

图片来源优先级

1️⃣ 公共领域作品(最优先)
  • 来源:Wikimedia Commons、Google Arts & Culture
  • 适用:经典艺术作品、历史人物肖像、古籍封面
  • 优点:免费、无版权问题、高质量
  • 示例:梵高《星空》、康德肖像
  • 操作:WebFetch获取Wikimedia Commons图片链接
2️⃣ AI生成(推荐)
  • 来源:火山引擎 doubao-seedream-4-0-250828
  • 适用:题图、概念图、抽象主题
  • 优点:原创、可定制、快速
  • 操作:调用API生成图片,返回临时URL
3️⃣ 免费图库
  • 来源:Unsplash、Pexels、Pixabay
  • 适用:题图、概念图、背景图
  • 优点:免费、高质量、商业可用(CC0)
  • 操作:WebFetch搜索 + 下载
4️⃣ 截图/官方素材(需注明来源)
  • 来源:YouTube、B站、产品官网、电影海报
  • 适用:案例图(产品截图、视频截图)
  • 注意:注明来源,合理使用原则
  • 操作:提醒用户自行截图,或生成AI概念图替代

图床上传流程

核心脚本

使用项目已有的 /tools/upload_image.py 脚本

上传方式
python
# 调用上传脚本(在Bash中)
python3 /Users/alchain/Documents/写作/tools/upload_image.py <图片URL或本地路径>

# 处理网络图片(如AI生成的临时链接)
python3 /Users/alchain/Documents/写作/tools/upload_image.py "https://example.com/ai-generated.jpg"

# 处理本地图片
python3 /Users/alchain/Documents/写作/tools/upload_image.py "/Users/alchain/Pictures/image.png"

# 脚本自动返回ImgBB永久链接
容错机制
  • ✅ 优先上传到ImgBB图床(永久有效)
  • ⚠️ 上传失败时,自动使用原链接作为fallback
  • 📌 详见 /tools/README.md - 图片上传脚本说明

Markdown插入格式

markdown
![图片描述](https://i.ibb.co/xxxxx/image.jpg)
  • 使用永久网络链接(不是本地路径)
  • 填写有意义的图片描述(alt text)
  • 图片描述要简洁,突出图片内容

图片规范

尺寸规范
  • 封面图:1200x600px (16:9)
  • 正文图:800-1200px宽
  • 人物/产品:800x800px (1:1)
文件规范
  • 格式:JPG(照片)/ PNG(插画)
  • 大小:< 500KB
  • 命名:小写、语义化、英文(如 mrbeast.jpg, starry-night.jpg)
路径规范
  • ✅ 网络链接:https://i.ibb.co/xxxxx/image.jpg(推荐,永久有效)
  • ❌ 本地路径:不再使用本地路径(复制到公众号会失效)

版权注意事项

  • ✅ 公共领域作品(作者去世70年以上)
  • ✅ CC0许可的图片(Unsplash等)
  • ✅ AI生成的图片(确认工具许可)
  • ⚠️ 截图/官方素材需注明来源

配图检查清单

执行配图任务前,确认以下事项:

  • 文章已审校完成,内容稳定
  • 确定配图数量(5-8张)
  • 确定配图位置(题图+核心章节)
  • 所有图片已获取(AI生成/公共领域/免费图库)
  • 所有图片已上传到ImgBB图床
  • 图片链接为永久网络链接(https:// 开头)
  • 已在Markdown中插入图片(使用网络链接)
  • 图片描述(alt text)已填写
  • 所有图片链接验证通过(可正常访问)

执行步骤(5步标准流程)

Step 1: 分析文章,确定配图需求
  • 通读全文,标记重点章节
  • 列出配图需求清单(6-8项)
  • 确定每张图的位置和作用
Step 2: 获取/生成图片

根据图片来源优先级获取图片:

  1. 公共领域作品 → WebFetch获取
  2. AI生成 → 调用API生成
  3. 免费图库 → WebFetch搜索
  4. 截图素材 → 提醒用户提供
Step 3: 上传到图床,获取永久链接
bash
# 对每张图片调用上传脚本
python3 /Users/alchain/Documents/写作/tools/upload_image.py <图片URL>
Step 4: 在文章中插入图片
markdown
![图片描述](https://i.ibb.co/xxxxx/image.jpg)
Step 5: 验证显示
bash
# 检查所有图片引用
grep -n "!\[" "文章路径.md"
# 所有图片链接应该是 https:// 开头的网络链接

参考资源

  • /tools/README.md - 图片上传脚本使用说明
  • /tools/upload_image.py - 图片上传脚本
  • /公众号写作/AI文生图API调用.md - AI文生图API说明
  • /公众号写作/images/useless-content/配图Best Practice总结.md - 配图最佳实践

常见问题

Q1: AI生成的图片临时链接会失效吗?

A: 会。所以必须调用upload_image.py上传到ImgBB,获取永久链接。

Q2: 如果图床上传失败怎么办?

A: 脚本有容错机制,会自动fallback到原URL。但建议检查ImgBB API配置。

Q3: 每篇文章必须配图吗?

A: 推荐配图,特别是长文(3000字以上)。但短文(1000字以下)可以只配题图。

Q4: 可以使用本地图片路径吗?

A: 不推荐。本地路径在复制到公众号编辑器后会失效,必须使用网络链接。

技术依赖

  • Python脚本: /tools/upload_image.py(已有)
  • API配置: ImgBB API key(已配置在 ~/.zshrc)
  • AI生成API: 火山引擎 doubao-seedream(可选)
  • 工具: WebFetch(获取公共领域图片)

成功案例

  • 《为什么最好的内容都是无用的》:6张配图(2张公共领域 + 4张AI生成)
  • 《DeepSeek-OCR深度评测》:5张配图,全部上传到ImgBB,复制到公众号无压力

最后更新: 2025-11-07 适用项目: 公众号写作 维护者: 花生


花叔出品 | AI Native Coder · 独立开发者 公众号「花叔」| 30万+粉丝 | AI工具与效率提升 代表作:小猫补光灯(AppStore付费榜Top1)·《一本书玩转DeepSeek》

© alchaincyf, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in huashu-image-upload of alchaincyf/huashu-skills.

Open the folder on GitHubat commit 2efea35

Compare with similar skills

Huashu Image Upload next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Huashu Image Upload compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Huashu Image Upload this skillalchaincyf/huashu-skills1.7k—~989Automated safety check: PassMIT
Markdown Article FormatterJimLiu/baoyu-skills27k6 repos~3.5kAutomated safety check: PassMIT
MarkitdownImCa0/just-laws78114 repos~3.2kAutomated safety check: NotesMIT
Obsidian MarkdownAtmosphere/atmosphere3.8k20 repos~1.3kAutomated safety check: PassApache-2.0
Crosspostingwasp-lang/wasp19k—~1.1kAutomated safety check: PassMIT
Gzh Designisjiamu/gzh-design-skill4k—~2.2kAutomated safety check: PassAGPL-3.0

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Works with

Questions about Huashu Image Upload

What does Huashu Image Upload do?

文章配图一键生成并上传图床,自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。. Huashu Image Upload is an agent skill from alchaincyf/huashu-skills.

When should I use Huashu Image Upload?

Huashu Image Upload fits situations like: tasks that involve Markdown.

How do I install Huashu Image Upload in Claude Code?

Run `npx skills add alchaincyf/huashu-skills --skill huashu-image-upload -a claude-code`. Or copy the skill folder (huashu-image-upload in alchaincyf/huashu-skills) into .claude/skills/huashu-image-upload in your project. Claude Code loads it when a task matches its description.

How do I install Huashu Image Upload in Codex?

Run `npx skills add alchaincyf/huashu-skills --skill huashu-image-upload -a codex`. Or copy the skill folder (huashu-image-upload in alchaincyf/huashu-skills) into .agents/skills/huashu-image-upload in your project. Codex loads it when a task matches its description.

Can I use Huashu Image Upload in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alchaincyf/huashu-skills --skill huashu-image-upload -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/huashu-image-upload, .gemini/skills/huashu-image-upload, .github/skills/huashu-image-upload and .opencode/skills/huashu-image-upload in your project.

What does Huashu Image Upload need to run?

Going by SKILL.md and its folder, Huashu Image Upload needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Huashu Image Upload access the network?

SKILL.md names 1 domain. In commands or code: i.ibb.co; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Huashu Image Upload safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Huashu Image Upload use?

Huashu Image Upload is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Huashu Image Upload use?

About 989 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Huashu Image Upload?

Skills that share tags, products or a category with Huashu Image Upload: Markdown Article Formatter (JimLiu/baoyu-skills, 27k stars), Markitdown (ImCa0/just-laws, 781 stars), Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars) and Crossposting (wasp-lang/wasp, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Huashu Image Upload?

alchaincyf (a GitHub user) maintains it in alchaincyf/huashu-skills, which has 1,695 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 22, 2026.

Source: alchaincyf/huashu-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.