WeWrite — WeChat AI Publishing Skill Skill by ara.so — Daily 2026 Skills collection. WeWrite is a full-pipeline AI skill for producing WeChat Official Account (公众号) articles end-to-end: hotspot fetching → topic selection → writing → SEO → AI image generation → formatting → draft box publishing. It runs as a Claude Code skill (via SKILL.md ) but every component also works standalone. Installation As a Claude Code Skill

Clone the repo

git clone https://github.com/oaker-io/wewrite.git ~/.claude/skills/wewrite

Or copy into an existing project

cp -r wewrite ~/.claude/skills/wewrite Python Dependencies cd wewrite pip install -r requirements.txt Configuration cp config.example.yaml config.yaml Edit config.yaml : wechat : appid : "${WECHAT_APPID}"

WeChat Official Account App ID

secret : "${WECHAT_SECRET}"

WeChat Official Account Secret

image_gen : provider : "doubao"

"doubao" or "openai"

doubao_api_key : "${DOUBAO_API_KEY}" openai_api_key : "${OPENAI_API_KEY}" output_dir : "./output" Set environment variables instead of hardcoding secrets: export WECHAT_APPID = "wx1234567890abcdef" export WECHAT_SECRET = "your_secret_here" export DOUBAO_API_KEY = "your_doubao_key" export OPENAI_API_KEY = "sk-..." Triggering the Full Pipeline Once installed as a Claude Code skill, simply say: 用 demo 的配置写一篇公众号文章 Claude will execute all steps automatically using clients/demo/style.yaml as the client profile. You can also specify a client: 用 clients/tech-blog 的风格，围绕今日热点写一篇公众号文章，发布到草稿箱 Pipeline Steps & Scripts 1. Fetch Hotspots Scrapes real-time trending topics from Weibo, Toutiao, and Baidu. python3 scripts/fetch_hotspots.py --limit 20 python3 scripts/fetch_hotspots.py --limit 10 --json

JSON output

Output example:

[

{

"rank"

:

1

,

"title"

:

"DeepSeek R2 发布"

,

"source"

:

"weibo"

,

"heat"

:

98200

}

,

{

"rank"

:

2

,

"title"

:

"A股科技板块大涨"

,

"source"

:

"baidu"

,

"heat"

:

75300

}

]

2. SEO Keyword Analysis

Queries Baidu and 360 search suggestions to score keywords.

python3 scripts/seo_keywords.py

"AI大模型"

"科技股"

python3 scripts/seo_keywords.py

--json

"ChatGPT"

"人工智能"

Python usage:

from

scripts

.

seo_keywords

import

analyze_keywords

results

=

analyze_keywords

(

[

"AI大模型"

,

"大语言模型"

,

"GPT-5"

]

)

for

kw

in

results

:

print

(

f"

{

kw

[

'keyword'

]

}

score= { kw [ 'score' ] } , volume= { kw [ 'estimated_volume' ] } " ) 3. Topic Selection Claude reads references/topic-selection.md and generates 10 candidate topics scored on: 热度 (trending heat) 契合度 (client fit) 差异化 (differentiation) 4. Framework & Writing Claude reads references/frameworks.md (5 frameworks) and references/writing-guide.md (de-AI style rules), then writes the article adapted to the client's tone. 5. AI Image Generation

Cover image (recommended 900×383)

python3 toolkit/image_gen.py \ --prompt "科技感封面，蓝色光线，未来感" \ --output output/cover.png \ --size cover

Inline content image

python3 toolkit/image_gen.py \ --prompt "程序员在办公室工作，现代风格插画" \ --output output/img1.png \ --provider openai Python usage: from toolkit . image_gen import generate_image path = generate_image ( prompt = "AI机器人与人类握手，科技感插画" , output_path = "output/cover.png" , size = "cover" ,

"cover" (900x383) or "content" (800x600)

provider

"doubao"

"doubao" or "openai"

) print ( f"Generated: { path } " ) 6. Formatting — Markdown → WeChat HTML WeChat requires inline styles. The converter handles this automatically.

Preview in browser

python3 toolkit/cli.py preview article.md --theme professional-clean

Available themes

python3 toolkit/cli.py themes Python usage: from toolkit . converter import MarkdownConverter from toolkit . theme import load_theme theme = load_theme ( "tech-modern" ) converter = MarkdownConverter ( theme = theme ) with open ( "article.md" ) as f : markdown_content = f . read ( ) html = converter . convert ( markdown_content )

html is WeChat-ready with all inline styles

1. Publish to WeChat Draft Box python3 toolkit/cli.py publish article.md \ --cover output/cover.png \ --title "2026年AI大模型最新进展" \ --author "科技观察" Python usage: from toolkit . publisher import WeChatPublisher from toolkit . wechat_api import WeChatAPI api = WeChatAPI ( appid = os . environ [ "WECHAT_APPID" ] , secret = os . environ [ "WECHAT_SECRET" ] ) publisher = WeChatPublisher ( api = api )

Upload cover image first

media_id

api . upload_image ( "output/cover.png" )

Push to draft box

draft_id

publisher . create_draft ( title = "2026年AI大模型最新进展" , content = html_content ,

inline-styled HTML from converter

cover_media_id

media_id , author = "科技观察" , digest = "本文盘点2026年大模型最新进展..."

summary/excerpt

) print ( f"Draft created: { draft_id } " ) 8. Fetch Article Stats (回填数据) python3 scripts/fetch_stats.py --article-id "your_article_id" 9. Learn from Manual Edits python3 scripts/learn_edits.py \ --original output/draft.md \ --edited output/final.md \ --client demo Extracts style rules from diffs and appends them to the client's playbook. Client Configuration Each client lives in clients/{name}/style.yaml :

clients/my-tech-blog/style.yaml

name : "我的科技博客" industry : "科技/AI" topics : - "人工智能" - "大模型应用" - "编程技术" tone : "专业严谨，偶尔幽默，面向中级开发者" theme : "tech-modern" avoid : - "过度营销语言" - "绝对化表述" wechat : appid : "${WECHAT_APPID}" secret : "${WECHAT_SECRET}" Create a new client: mkdir clients/my-client cp clients/demo/style.yaml clients/my-client/style.yaml

Edit style.yaml for your client

Themes Theme Style professional-clean Clean professional (default) tech-modern Tech-forward blue/purple gradient warm-editorial Warm editorial tones minimal Minimal black/white python3 toolkit/cli.py themes

list all themes with previews

python3 toolkit/cli.py preview article.md --theme warm-editorial Custom theme (YAML):

toolkit/themes/my-theme.yaml

name : my - theme body : font-family : "'PingFang SC', sans-serif" font-size : "16px" color : "#333" line-height : "1.8" h2 : color : "#1a73e8" font-weight : "bold" border-left : "4px solid #1a73e8" padding-left : "10px" blockquote : background : "#f0f4ff" border-left : "3px solid #4285f4" padding : "12px 16px" color : "#555" Full Pipeline — Python Orchestration import subprocess import json import os from toolkit . converter import MarkdownConverter from toolkit . theme import load_theme from toolkit . publisher import WeChatPublisher from toolkit . wechat_api import WeChatAPI from toolkit . image_gen import generate_image

1. Fetch hotspots

result

subprocess . run ( [ "python3" , "scripts/fetch_hotspots.py" , "--limit" , "20" , "--json" ] , capture_output = True , text = True ) hotspots = json . loads ( result . stdout )

2. SEO analysis on top topics

from scripts . seo_keywords import analyze_keywords top_titles = [ h [ "title" ] for h in hotspots [ : 5 ] ] seo_scores = analyze_keywords ( top_titles )

3. (Claude selects topic, writes article — handled by SKILL.md)

After Claude produces article.md:

4. Generate cover

cover_path

generate_image ( prompt = "科技感封面图，蓝色渐变，数字化未来" , output_path = "output/cover.png" , size = "cover" , provider = os . environ . get ( "IMAGE_PROVIDER" , "doubao" ) )

5. Convert Markdown → WeChat HTML

theme

load_theme ( "tech-modern" ) converter = MarkdownConverter ( theme = theme ) with open ( "output/article.md" ) as f : html = converter . convert ( f . read ( ) )

6. Publish to draft box

api

WeChatAPI ( appid = os . environ [ "WECHAT_APPID" ] , secret = os . environ [ "WECHAT_SECRET" ] ) publisher = WeChatPublisher ( api = api ) media_id = api . upload_image ( cover_path ) draft_id = publisher . create_draft ( title = "选定标题" , content = html , cover_media_id = media_id , author = "作者名" ) print ( f"✅ Published draft: { draft_id } " ) References Claude Uses During Pipeline These files are read automatically by Claude when executing the skill: File Purpose references/topic-selection.md 10-topic scoring rules (heat × fit × differentiation) references/frameworks.md 5 article structure templates references/writing-guide.md Style rules, de-AI-ification techniques references/seo-rules.md WeChat SEO: title length, keyword density, tags references/visual-prompts.md Image generation prompt templates references/wechat-constraints.md WeChat HTML/CSS technical limits references/style-template.md Client style.yaml schema documentation Troubleshooting WeChat API 40001 / invalid credential

Access token expires every 2 hours — the API wrapper auto-refreshes,

but verify your appid/secret are correct:

python3 -c " from toolkit.wechat_api import WeChatAPI import os api = WeChatAPI(os.environ['WECHAT_APPID'], os.environ['WECHAT_SECRET']) print(api.get_access_token()) " Image generation fails

Test provider connectivity

python3 toolkit/image_gen.py \ --prompt "测试图片" \ --output /tmp/test.png \ --provider doubao

If doubao fails, switch to openai in config.yaml

Markdown conversion missing styles

Verify theme loads correctly

python3 -c "from toolkit.theme import load_theme; print(load_theme('tech-modern'))"

Preview output before publishing

python3 toolkit/cli.py preview article.md --theme tech-modern

Opens browser with rendered HTML

Hotspot fetch returns empty

Platforms occasionally change their APIs — run with verbose:

python3 scripts/fetch_hotspots.py --limit 5 --verbose

Check which sources are failing; the script supports weibo/baidu/toutiao independently

Article not appearing in draft box Ensure the WeChat account has 服务号 or 订阅号 API access enabled Check that your IP is whitelisted in the WeChat MP platform settings Draft box ( 草稿箱 ) requires draft.add API permission Quick Reference

Full standalone workflow

python3 scripts/fetch_hotspots.py --limit 20 --json

hotspots.json python3 scripts/seo_keywords.py --json "关键词1" "关键词2" python3 toolkit/image_gen.py --prompt "封面描述" --output cover.png --size cover python3 toolkit/cli.py preview article.md --theme tech-modern python3 toolkit/cli.py publish article.md --cover cover.png --title "标题"

Build playbook from historical articles

python3 scripts/build_playbook.py --client demo

Learn from edits

python3 scripts/learn_edits.py --original draft.md --edited final.md --client demo

Fetch article performance data

python3 scripts/fetch_stats.py --article-id "msgid_here"