Summarize new arXiv papers into notes with scheduled agents
Set Up an Automated Search Script. Task: Suggested implementation: Create a YAML configuration defining research subjects and keywords. Develop a Python script using Claude Code to query arXiv daily and Google Scholar weekly. The script must record paper identifiers to deduplicate results and output new findings into a dated Markdown digest. Human role involves reviewing the generated digest for relevance.; tools: Claude Code. Human role: The original post does not say how a person stayed involved.; limitations: Source reliability is secondary; specific error handling for API rate limits or network failures is not detailed. Integration uncertainty exists regarding Google Scholar's stability for automated scraping. Human approval is required before treating the script as production-ready. Proposed advice: Implement robust logging for failed queries..
Tools
Published on Agent Work Atlas:
Overview
Set Up an Automated Search Script
Workflow
Suggested implementation: Create a YAML configuration defining research subjects and keywords. Develop a Python script using Claude Code to query arXiv daily and Google Scholar weekly. The script must record paper identifiers to deduplicate results and output new findings into a dated Markdown digest. Human role involves reviewing the generated digest for relevance.
Reported result
No measured outcomes or success metrics are reported in the source. The effectiveness of the deduplication logic and the quality of the Markdown digest remain unverified. A proposed acceptance check is to manually verify that zero duplicate papers appear in the digest over a one-week test period.
Human role
The original post does not say how a person stayed involved.
Limitations
Source reliability is secondary; specific error handling for API rate limits or network failures is not detailed. Integration uncertainty exists regarding Google Scholar's stability for automated scraping. Human approval is required before treating the script as production-ready. Proposed advice: Implement robust logging for failed queries.
Try it
Act as a research automation engineer. I need a Python script to automate academic paper discovery. [replaceable inputs: YAML file with topics/keywords, output directory for Markdown files]. Use Claude Code to generate the script. Steps: 1. Parse the YAML config. 2. Query arXiv API daily and Google Scholar weekly. 3. Maintain a local JSON file of seen paper IDs for deduplication. 4. Write new results to a dated Markdown file with title, authors, abstract, and link. 5. Include cron setup instructions. Quality check: Run a dry test with 5 sample papers. Verify no duplicates are written. Stop and ask for confirmation if API errors occur. Do not publish or send any notifications without my explicit approval.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.