# Wechat To Notion

> Save WeChat public account articles to a Notion database. Use when user sends a mp.weixin.qq.com link and wants to save/archive it to Notion. Fetches title, cover image, body content (paragraphs, headings, images, code blocks, lists) and writes them as Notion blocks.

- Skill: `dvcrn/wechat-to-notion` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add dvcrn/wechat-to-notion`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/wechat-to-notion/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/dvcrn/wechat-to-notion

---


# wechat-to-notion

Save a WeChat article to Notion in three steps: fetch → analyze → save.

## Configuration Check (Do This First)

Check if the Notion API key is configured:

```bash
echo ${NOTION_API_KEY:0:8}...
```

**If missing**, tell the user:

> You haven't configured a Notion API key yet:
> 1. Go to https://notion.so/my-integrations → **+ New integration** → copy the key (starts with `ntn_`)
> 2. Open your Notion database → **...** → **Connect to** → select your integration
> 3. Set the key in your OpenClaw config — **do not paste it into chat**:
>    ```
>    openclaw config set skills.entries.notion.apiKey "ntn_xxx"
>    ```
>    OpenClaw will inject it as `NOTION_API_KEY` automatically.

⚠️ Never ask the user to send the API key as a chat message — it will be exposed in conversation logs.

## Setup (One-time)

Ask if the user has an existing Notion database. If yes, use it directly. If no, ask for a parent page URL and create one:

```bash
curl -s -X POST https://api.notion.com/v1/databases \
  -H "Authorization: Bearer $NOTION_API_KEY" \
  -H "Notion-Version: 2025-09-03" \
  -H "Content-Type: application/json" \
  -d '{
    "parent": {"type": "page_id", "page_id": "<parent_page_id>"},
    "title": [{"type": "text", "text": {"content": "WeChat Articles"}}],
    "properties": {
      "Title": {"title": {}},
      "URL": {"url": {}},
      "Read Time": {"date": {}},
      "Tags": {"multi_select": {}},
      "Notes": {"rich_text": {}}
    }
  }'
```

> Match field names to the user's language (e.g. Chinese users get Chinese field names).

## Workflow

### Step 1: Fetch article

```bash
python3 {skillDir}/scripts/fetch_wechat.py <wechat_url> > /tmp/wx_article.json
```

### Step 2: Analyze (inline — reason directly, no subprocess)

Use the `read` tool to load `/tmp/wx_article.json`. Read the `title` and text content from `blocks`, then produce two outputs by reasoning directly:

**Keywords (3–5):**
- Lead with proper nouns: product names, tool names, frameworks, technical terms (e.g. Claude Code, MCP, OpenClaw, RAG)
- Add domain-specific concepts only when they add meaning (e.g. multi-agent orchestration, agentic workflow)
- Omit generic filler (e.g. "AI", "efficiency", "productivity", "tools")
- Comma-separated, preserve original casing

**Comment (1 sentence, written in the user's language):**
Write a single sentence structured in two parts:
1. A tight, neutral distillation of the article's core argument — precise enough to serve as a standalone summary quote
2. A parenthetical editorial aside: a sharp, specific take on the piece — its quality, angle, or the author's intent. Be direct. No hedging.
- Example: "MCP bridges OpenClaw and Claude Code, eliminating manual context-passing between agents (well-executed tutorial — the headline actually holds up)"
- Keep it under 35 words

### Step 3: Save to Notion

```bash
python3 {skillDir}/scripts/save_to_notion.py \
  /tmp/wx_article.json \
  <notion_db_url> \
  <wechat_url> \
  <read_time_iso8601+08:00> \
  "<kw1>,<kw2>,<kw3>" \
  "<comment>"
```

- `read_time`: current time in the user's local timezone as ISO 8601 with offset, e.g. `2026-03-12T14:00:00+08:00`
- `keywords`: comma-separated string
- `comment`: the single-sentence comment from Step 2

The script auto-detects field names from the database schema by type (`title`, `url`, `date`, `multi_select`), writes all content blocks in batches of 100, and posts the comment to the Notion Comments panel.

## Notes

- Cover image: extracted from `og:image` meta tag, inserted as the first block
- Rich text (bold/italic), code blocks, and lists are preserved by `fetch_wechat.py`
- Read time defaults to current system time with local UTC offset if omitted
- The comment appears in the Notion Comments panel, not in the page body
- Field names are language-agnostic — the script maps by type, not by name