Run literature reviews over a folder of papers
Have you ever felt that "reading papers takes too much time, and my actual research isn't progressing"? Task: Have you ever felt that "reading papers takes too much time, and my actual research isn't progressing"? Literature reviews, organizing prior research, and grasping citation relationships. These are all essential tasks for research, but doing them manually consumes a vast amount of time. Many of you have likely pasted papers into ChatGPT to have them summarized. However, as you repeat the process of copying and pasting one paper after another, you must have felt, "Isn't there a way to make this more efficient?" With Claude Code, you can read an entire folder full of PDFs and automatically organize citation relationships, research trends, and the connections to your own research. In this article, I will introduce how researchers and graduate students can use Claude Code to transform their literature reviews, along with concrete ways to use it. The Current Situation and Challenges for Researchers and Graduate Students Writing papers, presenting, and reporting progress to supervisors. Research activities involve a lot of "writing work." The literature review that precedes this is a task that particularly drains time and focus. Typical concerns probably look something like this: There are over 50 related papers, and I can't read them all, causing me to overlook important prior research There are over 50 related papers, and I can't read them all, causing me to overlook important prior research It takes time to organize citation relationships and the flow of research in my head It takes time to organize citation relationships and the flow of research in my head It is cumbersome to rethink "how does this paper relate to my research theme" every single time It is cumbersome to rethink "how does this paper relate to my research theme" every single time My supervisor points out that my "literature review is weak," but I haven't organized how or what I should be reading My supervisor points out that my "literature review is weak," but I haven't organized how or what I should be reading Many of you have likely tried using ChatGPT. It is certainly helpful when you paste one paper and ask it to "summarize this." But the problem is that it can only process one at a time. The task of pasting 50 papers one by one to get summaries and then summarizing them yourself ends up consuming several hours before you realize it. This is where Claude Code is different. If you specify a folder, it can read and process all the papers inside at once. What is Claude Code? (Basic Explanation) Claude Code is an AI coding tool developed by Anthropic. It is not an AI that you talk to in a browser, but an AI that you run from your PC's terminal (command line). The fact that it "runs from the terminal" is a major difference. While ChatGPT only returns text, Claude Code can directly read files on your computer, organize them, and save them as new files. You don't need programming knowledge. It works just by giving instructions in Japanese, such as "Read this paper folder and create a list of their relevance to my research theme." [Core] What Only Claude Code Can Do 1. Can process papers by the folder This is the biggest point of differentiation. ChatGPT and Gemini can basically only handle one file at a time. Claude Code accepts instructions like "Read all PDFs in the papers/ folder." If you specify 50 papers, you can perform an analysis that spans all 50. 2. Can turn literature reviews into a single command using Skills (slash commands) By typing /literature-review, you can create your own custom tool that runs a sequence of processes: "read folder -> extract key points -> score relevance to my research -> format into a list and save." You don't need to input the same instructions every time; once you create it, you can reuse it as many times as you like. 3. You can have it memorize your research context with CLAUDE.md By writing your research theme, keywords, supervisor feedback, and academic terminology in CLAUDE.md, it will process information based on your context without you having to explain "I am researching XXX" every time. 4. You can automatically collect new papers every week with scheduled execution By linking with Google Scholar or arXiv APIs, you can automate the process of "listing new papers in your research field published last week -> summarizing them -> assigning relevance scores -> notifying you on Slack" every Monday morning. It keeps running on its own every week without human intervention.; tools: Claude Code. Human role: The original post does not say how a person stayed involved.; limitations: Accuracy depends on PDF text extraction quality, with scanned images performing poorly. AI summaries are supplementary, requiring human validation for final research decisions. Copyright and institutional data policies must be checked before sending unpublished research to external APIs. The source is a promotional blog post, so performance claims may be optimistic..
Tools
Published on Agent Work Atlas:
Overview
Have you ever felt that "reading papers takes too much time, and my actual research isn't progressing"?
Workflow
Have you ever felt that "reading papers takes too much time, and my actual research isn't progressing"? Literature reviews, organizing prior research, and grasping citation relationships. These are all essential tasks for research, but doing them manually consumes a vast amount of time. Many of you have likely pasted papers into ChatGPT to have them summarized. However, as you repeat the process of copying and pasting one paper after another, you must have felt, "Isn't there a way to make this more efficient?" With Claude Code, you can read an entire folder full of PDFs and automatically organize citation relationships, research trends, and the connections to your own research. In this article, I will introduce how researchers and graduate students can use Claude Code to transform their literature reviews, along with concrete ways to use it. The Current Situation and Challenges for Researchers and Graduate Students Writing papers, presenting, and reporting progress to supervisors. Research activities involve a lot of "writing work." The literature review that precedes this is a task that particularly drains time and focus. Typical concerns probably look something like this: There are over 50 related papers, and I can't read them all, causing me to overlook important prior research There are over 50 related papers, and I can't read them all, causing me to overlook important prior research It takes time to organize citation relationships and the flow of research in my head It takes time to organize citation relationships and the flow of research in my head It is cumbersome to rethink "how does this paper relate to my research theme" every single time It is cumbersome to rethink "how does this paper relate to my research theme" every single time My supervisor points out that my "literature review is weak," but I haven't organized how or what I should be reading My supervisor points out that my "literature review is weak," but I haven't organized how or what I should be reading Many of you have likely tried using ChatGPT. It is certainly helpful when you paste one paper and ask it to "summarize this." But the problem is that it can only process one at a time. The task of pasting 50 papers one by one to get summaries and then summarizing them yourself ends up consuming several hours before you realize it. This is where Claude Code is different. If you specify a folder, it can read and process all the papers inside at once. What is Claude Code? (Basic Explanation) Claude Code is an AI coding tool developed by Anthropic. It is not an AI that you talk to in a browser, but an AI that you run from your PC's terminal (command line). The fact that it "runs from the terminal" is a major difference. While ChatGPT only returns text, Claude Code can directly read files on your computer, organize them, and save them as new files. You don't need programming knowledge. It works just by giving instructions in Japanese, such as "Read this paper folder and create a list of their relevance to my research theme." [Core] What Only Claude Code Can Do 1. Can process papers by the folder This is the biggest point of differentiation. ChatGPT and Gemini can basically only handle one file at a time. Claude Code accepts instructions like "Read all PDFs in the papers/ folder." If you specify 50 papers, you can perform an analysis that spans all 50. 2. Can turn literature reviews into a single command using Skills (slash commands) By typing /literature-review, you can create your own custom tool that runs a sequence of processes: "read folder -> extract key points -> score relevance to my research -> format into a list and save." You don't need to input the same instructions every time; once you create it, you can reuse it as many times as you like. 3. You can have it memorize your research context with CLAUDE.md By writing your research theme, keywords, supervisor feedback, and academic terminology in CLAUDE.md, it will process information based on your context without you having to explain "I am researching XXX" every time. 4. You can automatically collect new papers every week with scheduled execution By linking with Google Scholar or arXiv APIs, you can automate the process of "listing new papers in your research field published last week -> summarizing them -> assigning relevance scores -> notifying you on Slack" every Monday morning. It keeps running on its own every week without human intervention.
Reported result
The author reports that batch literature review time dropped from 2-3 days to 30 minutes, and citation network organization from 4-5 hours to 15 minutes. Weekly new paper monitoring time was reduced from 1-2 hours to zero via automated notifications. These metrics are self-reported by the source and lack independent verification or detailed methodology.
Human role
The original post does not say how a person stayed involved.
Limitations
Accuracy depends on PDF text extraction quality, with scanned images performing poorly. AI summaries are supplementary, requiring human validation for final research decisions. Copyright and institutional data policies must be checked before sending unpublished research to external APIs. The source is a promotional blog post, so performance claims may be optimistic.
Try it
I want to automate my literature review using Claude Code. My research topic is [replaceable input: e.g., LLM alignment]. I have a folder of PDFs at [replaceable input: path/to/papers]. First, create a CLAUDE.md file with my research keywords and supervisor feedback. Then, write a skill command /lit-map that reads all PDFs in the folder, extracts objectives and methods, scores relevance against my context, and saves a Markdown summary to literature_map.md. Run this on a sample of 5 papers first. Show me the output for human review before processing the full folder. Do not send any data to external APIs without my explicit confirmation. If text extraction fails for any PDF, list the filenames and stop.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.