Claude God Tip #16: Stop Googling Like It's 2010 (The Research Tool)
Published: December 20, 2025 • 9 min read
In two previous blog posts, I casually mentioned the research tool in Claude. I talked about it when I introduced Alex Bennett, my Chief Marketing Officer, and then again in this blog post where I admitted I was tempted to use the research tool as a sophisticated way of procrastinating the 777-1 Experiment.
Since I want to cover all bases with my Claude God tips series, it is important that I talk extensively about this feature and why you should be using it. Consider this to be a big Claude God Tip. Let's dive into it!
The Problem with How Most People Use Claude
Claude's research tool is a very useful feature that I believe most Claude users do not take advantage of, or even understand how it works.
LLMs, like Claude, are trained on a really, really large dataset usually dated up until a certain date. This means that when you ask Claude questions, it is usually retrieving information from this very large dataset that it has been trained on. This explains why Claude sometimes messes up with dates when providing information. Now there is obviously a tool, the web_search tool, that Claude uses to access even more recent data that it has not been trained on. This way, Claude can still provide answers based on more up-to-date information.
Now that you are aware of the two above, what makes the Research feature special? Does it just use the web_search tool to provide deeper answers?
Well no, not really. It is a lot more robust and sophisticated than that.
What Actually Happens When You Launch Research
When you activate Research, Claude does not just search the web once to retrieve all the relevant data. It instead triggers an entire orchestration system with multiple agents working in parallel to fulfill your research requests.
If you have used the research tool before, just by simply observing it, you will notice the following:
- It starts by interpreting your query and creating a research strategy using the Lead Orchestrator Agent
- Then it gathers multiple sources, usually over 100 sources based on the questions asked, and then assigns different and specific aspects of your question to Multiple Search Sub-Agents
- Then it creates a final report and has a Citation Agent format the references so that you can validate the claims yourself in that report
Here is a more detailed breakdown of what happens when you launch a research session:
Stage 1: Query Decomposition
- Orchestrator breaks your question into sub-questions
- Identifies temporal context (is this about recent events or historical?)
- Determines technical depth required
- Plans search strategy
Stage 2: Parallel Research
- Sub-agents execute simultaneous searches
- Each search can trigger follow-up searches
- Real-time filtering of low-quality sources
- Cross-referencing across multiple sources
Stage 3: Synthesis and Validation
- Integration of findings into narrative
- Confidence rating for each claim
- Controversy identification
- Gap analysis (what's still unknown)
Stage 4: Citation and Delivery
- Source quality assessment
- APA-style formatting
- Visual element creation (charts, diagrams)
- Final report assembly
You can see from the breakdown above that using the Research tool is almost like having multiple PhD-level specialists in certain subject areas dissect your question thoroughly. They sift out low-quality sources when deciding how to respond to you, with the different sub-agents acting almost like they are peer-reviewing the sources before finally providing its final output to you. For students, using this tool would replace the 47 browser tabs you have open when completing a research assignment essay, for instance.
How I Actually Use This Feature
I used this Research feature to gather all the relevant data I needed about LinkedIn's 360Brew algorithm as I am trying to establish dominance in the field of AI on LinkedIn. Alex Bennett has access to this file and uses it when informing the decisions I make about what to post, when to post, and ideal content format. Alex does a lot more than these, but I will save the details about that for a future post.
The Feature Most People Miss: Restricting Sources
Now, one thing that most Claude users, even people who have tried the Research tool, may not realize is that you are not limited to information on the web when using the Research tool.
Claude allows you to connect external services like Google Drive, Gmail, Google Calendar, GitHub, etc. to specific projects or chats. This means that you can launch the research tool and request that all sources used in that research should be restricted to YOUR Google Workspace, perhaps your Google Drive, Google Calendar, or a combination of all of them.
Here are some practical examples:
For Students:
Research my study materials on Google Drive for everything related to mitochondrial function and create a study guide for my biology exam next week.
For Remote Workers:
Search my Gmail and Google Calendar from the past month. Summarize all action items I've committed to in meetings that I might have forgotten about.
For Managers:
Search our team's shared Google Drive for all project documentation related to the Q4 launch. Create a status report identifying what's complete, what's in progress, and what's at risk.
Time-Constrained Research
You can also use your prompts to restrict the amount of time you want the research to take, especially if you do not want the research to last too long. In this case, your prompt may look something like one of the following:
Quick 2-Minute Research:
Do a quick 2-minute research on the best protein sources for muscle recovery after workouts. Just give me the top 5 options with brief explanations.
Focused 5-Minute Deep Dive:
Spend about 5 minutes researching the current scientific consensus on intermittent fasting for weight loss. Focus only on peer-reviewed sources from the last 3 years.
Comprehensive 10-Minute Analysis:
Take up to 10 minutes to research the pros and cons of different morning workout routines. Compare 5 AM workouts vs. after-breakfast workouts based on scientific evidence.
Lazy Prompts vs. Intentional Prompts
Now, knowing that you have a research tool does not mean that the quality of your prompts does not affect the type of results returned by the research tool.
There is a difference between using the lazy prompt:
Research high-protein breakfast ideas
Versus the intentional prompt:
Research high-protein breakfast ideas. Prioritize:
- Nutrition sources with actual protein gram counts
- Recipes that take under 15 minutes to prepare
- Scientific sources on protein absorption timing
- Recent studies (2024-2025) on breakfast protein needs
Flag anything that seems like bro-science or lacks citations.
See the difference? The second prompt tells the research tool exactly what quality standards you expect, what time constraints matter, and even what to flag as potentially unreliable. You are essentially giving instructions to those PhD-level sub-agents I mentioned earlier.
How to Enable Research
The web_search tool must always be activated when using Claude's research tool. You can do so by clicking on the plus icon in the text input area and clicking on "Web Search". You can also enable the Research tool in the same manner. If you enable the Research tool without the Web Search tool being enabled, it will automatically be enabled as the research tool cannot work without it.
Context Window Warning
I mentioned earlier that a single research session could pull from multiple different sources, many times over 100 different sources. You can imagine that loading all of these sources into a single context window will cost a lot of tokens.
If you have read my posts on tokens and context windows, you know why this matters. Therefore, I recommend that you start a new conversation every time you need to perform research to ensure that there is enough context window available to retrieve all the information needed for that research.
Coming Soon: The Research Prompt Template
Now, I will stop here for now in this blog post. However, in a future blog post, I will provide you with a prompt template, one that allows you to write solid research prompts for different use cases so that you are not using lazy prompts like the first example I showed above, but instead, writing more intentional prompts.
When that is ready, you should be able to access it here.
As always, thanks for reading!