Aws Wechat Sticker logo

Aws Wechat Sticker

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aiworkskills
aws-wechat-sticker

公众号贴图|九宫格|多图推送|图片消息|表情包 — 贴图与多图推送:从创意构思、规划图序、AI 生图到整组图审核,产出一组风格统一的图片 + 每张配文。发布走常规图文链路(拼成图文后 formatting + publish),微信原生「图片消息」需在公众号后台手动发。面向公众号运营、自媒体、IP 账号。触发词:「贴图」「多图推送」「发组图」「图片消息」「九宫格」「做一组图」「图片帖子」「发几张图」「不写正文发图」「只发图不写字」。是文章内配图/封面请走 aws-wechat-article-images;需要多环节串联(写+审+排+配图+发)请走 aws-wechat-article-main。

Overview

Publisheraiworkskills
Repositorywechat-article-skills
Skill nameaws-wechat-sticker
Stars
672
Forks
99
Bundled files
4
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aiworkskills on GitHub. Read the source before you install it.

Installation

Install the Aws Wechat Sticker AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aiworkskills/wechat-article-skills/tree/main/skills/aws-wechat-sticker
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aiworkskills/wechat-article-skills.git /tmp/wechat-article-skills
mkdir -p .claude/skills
cp -r /tmp/wechat-article-skills/skills/aws-wechat-sticker .claude/skills/aws-wechat-sticker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Wechat Sticker in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Wechat Sticker on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Wechat Sticker is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

贴图 / 多图推送

一组风格统一的图 + 每张配文 —— 构思、排图序、生图、审图。

套件说明 · 本 skill 属 aws-wechat-article-* 一条龙套件(共 9 个 slug,入口 aws-wechat-article-main)。跨 skill 的相对引用依赖同一 skills/ 目录,建议一并 clawhub install 全套。源码:https://github.com/aiworkskills/wechat-article-skills

能力披露(Capabilities)

本 skill 编排贴图流程,调用同套件的 image_create.py(images)生图;可选调用 publish.py 发布。会把图片 prompt 发给外部图像 API;若走发布路径,会把图片作为 POST body 上传到微信 API。

  • 凭证读取:aws.env 的 IMAGE_MODEL_API_KEY;走发布时额外读 WECHAT_{N}_APPID / WECHAT_{N}_APPSECRET
  • 凭证外发:IMAGE_MODEL_API_KEY 以 Authorization: Bearer 头发给 image_model.base_url;微信凭证用于换 access_token
  • 内容外发:图片 prompt 发给图像 API;图片文件发给微信 material/add_material / draft/add
  • 文件读:.aws-article/config.yaml、本篇 article.yaml、imgs/prompts/*.md
  • 文件写:本篇 imgs/*.{png,webp}、imgs/outline.md、article.yaml
  • shell:{python} {baseDir}/../aws-wechat-article-images/scripts/image_create.py;可选 ../aws-wechat-article-publish/scripts/publish.py

至少要同时装 aws-wechat-article-images(生图能力在那边);要走发布再装 aws-wechat-article-publish。

路由

长文图文(标题+正文+插图+后台发文)→ aws-wechat-article-main;长文内单篇插图 → aws-wechat-article-images。本 skill 做以图片为主的内容:多张图 + 每张配文,整组统一风格。

产出目标(先看这个)

  • 输入:主题 / 选题卡 / 用户素材图(任选其一)
  • 输出:imgs/(outline.md + prompts/ + 图片),整组风格统一,不漂移
  • 发布:⛔ 微信原生「图片消息」本套件未实现。要么把整组图拼成一篇图文走常规链路,要么只交付图由用户在后台手发——两条路径见 branches.md「一」

配置检查 ⛔

任何操作前先按 首次引导 · 检测顺序 执行,通过后才继续(或用户明确书面确认「本次不检查」)。

图片模型:image_model(provider、base_url、model)在 .aws-article/config.yaml;IMAGE_MODEL_API_KEY 在仓库根 aws.env。键名对照 env.example.yaml。

须遵守 main 的智能体行为约束:未通过环境校验且未获用户明确「本次例外」时,不得假装已走专用生图 API。

工作流

贴图进度:
- [ ] 第1步:⛔ 环境检查 + 合并本篇约束
- [ ] 第2步:确定选题
- [ ] 第3步:确定风格(全组统一)
- [ ] 第4步:规划图序 → imgs/outline.md
- [ ] 第5步:⛔ 展示方案并等用户确认
- [ ] 第6步:生成图片
- [ ] 第7步:审图
- [ ] 第8步:交付(拼图文发 或 交给用户后台手发)

第1步:合并本篇约束

本篇在 drafts/…/ 下时,按 .aws-article/config.yaml → 本篇 article.yaml 合并读取(同键本篇优先)。重点字段:multi_image_count、tone、target_reader、custom_sticker_style > default_sticker_style。

无有效 YAML 时,用用户口述主题 + skill 默认值。

第2步:确定选题

topics 产出的贴图卡片 / 用户直接给主题 / 用户提供素材图。

第3步:确定风格

加载优先级与九个形态的分类(信息位 5 个 / 节奏位 3 个)见 branches.md「三」。

全组图统一一个形态 —— 组图的价值就在整齐,每张换一个等于没有风格。

第4步:规划图序

产出 imgs/outline.md:每张图的用途、配文、文件名。模板见 references/workflow.md;贴图类型与叙事线见 branches.md「四」。

张数 ≤ 9(微信限制)。

第5步:展示方案并等用户确认 ⛔

把 outline.md 整张表摆给用户,等确认再生图——生图要花钱,方案错了每张都得重来。

第6步:生成图片

优先调 image_create.py(依赖 image_model + IMAGE_MODEL_API_KEY);环境未就绪或用户接受 main 的「本次例外」时才降级为 Agent 生图 / 只出 prompts。

必须告知用户当前用的是哪种:

  • ℹ️ 使用 image_create.py 调用专用生图模型({model})
  • ℹ️ 本次未走 image_create.py(原因:…)

在仓库根执行(路径按本篇 imgs/ 调整):

bash
# 整批
{python} {baseDir}/../aws-wechat-article-images/scripts/image_create.py batch drafts/YYYYMMDD-slug/imgs/prompts/ -o drafts/YYYYMMDD-slug/imgs/

# 单张
{python} {baseDir}/../aws-wechat-article-images/scripts/image_create.py generate imgs/prompts/01.md -o imgs/01.png

# 连通性自检
{python} {baseDir}/../aws-wechat-article-images/scripts/image_create.py test

图片内文字与 prompt 构建规则与长文配图完全一致,见 images SKILL 与 prompt-construction.md。调用失败的四分类处理见 branches.md「二」。

第7步:审图

贴图专用清单:references/checklist.md。重点是整组看:风格是否统一、第一张缩略图下是否仍可辨、图序是否读得通。

第8步:交付

⛔ 不要在贴图目录上直接跑 publish.py full —— 它硬性要求 article.yaml + article.html + cover.*,贴图目录没有这三样,跑了必然报错。

两条落地路径(拼成图文自动发 / 只交付图由用户后台手发)见 branches.md「一」。走第二条时不要声称发布闭环完成。

分支与细则

发布路径的真实边界、生图失败四分类、风格与形态优先级、贴图类型与叙事线、「九宫格」指什么、单独安装 → references/branches.md。

过程文件

读取产出
topic-card.md(可选)、.aws-article/config.yaml + 本篇 article.yamlimgs/outline.md、imgs/prompts/*.md、imgs/*.png

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aws Wechat Sticker AI skill do?

公众号贴图|九宫格|多图推送|图片消息|表情包 — 贴图与多图推送:从创意构思、规划图序、AI 生图到整组图审核,产出一组风格统一的图片 + 每张配文。发布走常规图文链路(拼成图文后 formatting + publish),微信原生「图片消息」需在公众号后台手动发。面向公众号运营、自媒体、IP 账号。触发词:「贴图」「多图推送」「发组图」「图片消息」「九宫格」「做一组图」「图片帖子」「发几张图」「不写正文发图」「只发图不写字」。是文章内配图/封面请走 aws-wechat-article-images;需要多环节串联(写+审+排+配图+发)请走 aws-wechat-article-main。

Why use Aws Wechat Sticker on TypingMind?

Because you install it once and use it with any model. Aws Wechat Sticker is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Wechat Sticker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aiworkskills/wechat-article-skills/tree/main/skills/aws-wechat-sticker. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aws Wechat Sticker?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Wechat Sticker?

As many as you like. As long as a model supports skills, you can use Aws Wechat Sticker with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Wechat Sticker AI skill free?

Yes. It is published on GitHub by aiworkskills under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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