wewrite-wechat-ai-publishing

Original：🇺🇸 English

Translated

Full-pipeline AI skill for WeChat Official Account articles — hotspot fetching, topic selection, writing, SEO, image generation, formatting, and draft box publishing.

2installs

Sourcearadotso/trending-skills

Added on2026-03-28

NPX Install

npx skill4agent add aradotso/trending-skills wewrite-wechat-ai-publishing

SKILL.md Content

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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

bash

# 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

bash

cd wewrite
pip install -r requirements.txt

Configuration

bash

cp config.example.yaml config.yaml

Edit

config.yaml

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:

bash

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.

bash

python3 scripts/fetch_hotspots.py --limit 20
python3 scripts/fetch_hotspots.py --limit 10 --json   # JSON output

Output example:

json

[
  {"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.

bash

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:

python

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

bash

# 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:

python

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.

bash

# Preview in browser
python3 toolkit/cli.py preview article.md --theme professional-clean

# Available themes
python3 toolkit/cli.py themes

Python usage:

python

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

7. Publish to WeChat Draft Box

bash

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:

python

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)

bash

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

9. Learn from Manual Edits

bash

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

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:

bash

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

bash

python3 toolkit/cli.py themes          # list all themes with previews
python3 toolkit/cli.py preview article.md --theme warm-editorial

Custom theme (YAML):

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

python

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

bash

# 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

bash

# 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

bash

# 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

bash

# 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

bash

# 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"

wewrite-wechat-ai-publishing

NPX Install

Tags

SKILL.md Content

WeWrite — WeChat AI Publishing Skill

Installation

As a Claude Code Skill

Python Dependencies

Configuration

Triggering the Full Pipeline

Pipeline Steps & Scripts

1. Fetch Hotspots

2. SEO Keyword Analysis

3. Topic Selection

4. Framework & Writing

5. AI Image Generation

6. Formatting — Markdown → WeChat HTML

7. Publish to WeChat Draft Box

8. Fetch Article Stats (回填数据)

9. Learn from Manual Edits

Client Configuration

Themes

Full Pipeline — Python Orchestration

References Claude Uses During Pipeline

Troubleshooting

Quick Reference