Gemini Deep Research → Notion

Trigger Gemini Deep Research via browser and save results to Notion. Use when the user asks to "deep research" a topic, says "gemini deep research", or wants an in-depth research report. Execute ALL steps in the main session (browser tool requires main session access).

Execution Mode

Run ALL steps in the MAIN SESSION. Do NOT spawn a subagent.

The browser tool (OpenClaw managed profile) is only available in the main session. Subagents cannot access the browser, so all browser automation must happen here.

Reply first: "🔬 Deep Research starting for: [topic]. This takes ~25 min. I'll update you when done."

Then execute all phases below sequentially.

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Instructions

Complete ALL steps below in the main session.

Phase 1: Trigger Deep Research

1. browser action=open profile=openclaw targetUrl="https://gemini.google.com/app"
2. Snapshot, find the text input, type the research query. Always prepend "请用中文回答。" to the query so the research output is in Chinese.
3. Click "工具" (Tools) button (has page_info icon) → click "Deep Research" in the menu
4. Click Send to submit the query
5. Wait for research plan to appear (~10s), then click "Start research" / "开始研究" button
   • If snapshot-click doesn't work, use JS: (() => { var btn = Array.from(document.querySelectorAll('button')).find(b => /Start research|开始研究/.test(b.textContent.trim())); if (btn) { btn.click(); return 'clicked'; } return 'not found'; })()
6. Verify research started: button should be disabled, status shows "Researching X websites..." or "正在研究..."
7. Save the conversation URL from the browser

Phase 2: Wait for Completion

1. Run exec("sleep 1200") (20 minutes) + process(poll, timeout=1200000)
2. After waking, check status via JS: (() => { var el = document.querySelectorAll('message-content')[1]; return el ? el.innerText.substring(0, 200) : 'NOT_FOUND'; })()
3. Look for completion signals: "I've completed your research" or "已完成"
4. If still running, sleep another 600s and check again (max 2 retries)
5. If failed/stuck after retries, announce the failure and exit

Phase 3: Extract Report

1. Count message-content elements: document.querySelectorAll('message-content').length
2. The research report is in the LAST message-content element (usually index 2)
3. Get total length: document.querySelectorAll('message-content')[2]?.innerText?.length
4. Extract in 8000-char chunks using substring: document.querySelectorAll('message-content')[N]?.innerText?.substring(START, END)
5. Concatenate all chunks into the full report text
6. Save to a temp file: write full report to /tmp/deep_research_<timestamp>.md

Phase 4: Export to Notion

Parent page ID: 31a4cfb5-c92b-809f-9d8a-dd451718a017 (Deep Research Database)

1. Read the Notion API key: cat ~/.config/notion/api_key
2. Parse the report into Notion blocks:
   • Lines starting with # → heading_2/heading_3 blocks
   • Bullet points → bulleted_list_item blocks
   • Regular text → paragraph blocks
   • Add a callout at top: "🔬 Generated by Gemini Deep Research on YYYY-MM-DD"
   • Split rich_text at 2000 chars
3. Create the page via Notion API:

   curl -s -X POST "https://api.notion.com/v1/pages" \
     -H "Authorization: Bearer $NOTION_KEY" \
     -H "Notion-Version: 2025-09-03" \
     -H "Content-Type: application/json" \
     -d '{"parent":{"page_id":"31a4cfb5-c92b-809f-9d8a-dd451718a017"},"icon":{"type":"emoji","emoji":"🔬"},"properties":{"title":{"title":[{"text":{"content":"TOPIC"}}]}},"children":[BLOCKS]}'
   

4. If >100 blocks, append remaining via PATCH to /v1/blocks/{page_id}/children
5. Rate limit: wait 0.5s between batch requests

Phase 5: Announce

Report back with:

• Research topic
• Brief summary (2-3 key findings)
• Notion page URL: https://www.notion.so/<page_id_without_dashes>

Notes

• Always use profile="openclaw" for browser
• Deep Research is under "工具" (Tools) menu, NOT the model selector
• If Gemini needs login, announce failure — user must log in manually
• The full pipeline should complete in ~25-30 min total