Generate updated research reports on followed companies
The poster built and open-sourced a custom stock-research agent that produces updated reports on companies they follow. Task: Suggested implementation: Build a stock-research agent using real-time market data APIs (e.g., Polygon) to generate updated reports for followed companies. The workflow involves subscribing to data feeds, executing code for screening patterns (like inside-day), and producing reports. Human role: Define investment criteria, verify data accuracy against official filings, and approve final outputs.; tools: custom-built or unnamed agent. Human role: The original post does not say how a person stayed involved.; limitations: Prerequisites include paid real-time data subscriptions (e.g., Polygon) and coding capability. Operating costs involve API fees. Integration uncertainty exists regarding API rate limits and data latency. Source reliability is low due to inaccessible original post. Human approvals are required for all financial insights before use..
Tools
custom-built or unnamed agent
Published on Agent Work Atlas:
Overview
The poster built and open-sourced a custom stock-research agent that produces updated reports on companies they follow.
Workflow
Suggested implementation: Build a stock-research agent using real-time market data APIs (e.g., Polygon) to generate updated reports for followed companies. The workflow involves subscribing to data feeds, executing code for screening patterns (like inside-day), and producing reports. Human role: Define investment criteria, verify data accuracy against official filings, and approve final outputs.
Reported result
Actual outcomes are unknown as the source is inaccessible (HTTP 403). Proposed measurable acceptance check: Compare agent-generated report freshness and accuracy against manual research for 5 companies over 2 weeks. Success metric: 90% data accuracy and 50% reduction in research time.
Human role
The original post does not say how a person stayed involved.
Limitations
Prerequisites include paid real-time data subscriptions (e.g., Polygon) and coding capability. Operating costs involve API fees. Integration uncertainty exists regarding API rate limits and data latency. Source reliability is low due to inaccessible original post. Human approvals are required for all financial insights before use.
Try it
I want to build a stock-research agent for my portfolio. [replaceable inputs: list of 5 tickers, Polygon API key, output folder]. Steps: 1. Fetch real-time price and options data for each ticker. 2. Run Python code to identify 'inside-day' patterns. 3. Generate a one-page markdown report per company with key metrics. 4. Save to [output folder]. Measure quality by verifying data against Yahoo Finance. Handle missing data by logging errors. First, run a dry test on one ticker and show me the output for confirmation before processing the rest.
Source reports are not independently verified. Publication date is the catalog publication date, not the original article date.