Research a topic question by question
Turns a topic into the questions worth asking, searches each one, and files the findings in Notion with the source behind every line.
What it does
Each integration step this workflow runs, in order, what it is for, and the conditions and loops that decide when it runs.
- 1AnthropicGenerate model responseAsks the AI to break the topic into research questions, then to write one finding per numbered extract, each citing its number.
For each
question- 2Jina AISearch webSearches the web for each question in turn, collecting the title, address and description of every result as a numbered source.
- 2
- 3NotionCreate pageCreates a page in your Notion database titled with the research topic, writing no other property.
- 4NotionAppend block childrenFills the page with the questions asked, one sourced finding per line, the numbered source list and a coverage note.
How it works
What happens on each run, in plain English.
Give it a topic and run it, and the AI breaks it into the specific questions it raises. Each question is searched separately, the search results become numbered extracts, and the AI writes one finding per extract with its number on every line.
What you get is a new page in your Notion database, titled with your topic, holding the questions asked, the findings with a link on every line to its source, and a numbered list of the pages behind them. Nothing unsourced reaches the page: a finding citing a number that was never fetched is discarded, as is any line containing a web address, and at most one finding is kept per source. If the results carry too little text to write from, or every finding is discarded, the run stops and nothing is filed. The page ends with a count of sources used and lines dropped, so a thin run cannot pass for a thorough one.
Each run files a fresh page and touches nothing you already have. The database needs to be shared with your Notion integration.
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