AI Services Market › Use cases › Money, Bills & Benefits
Money, Bills & BenefitsDone with custom-built or unnamed agent 2026-10-24
Give stock screening live market context with a RAG agent
A commenter built a RAG agent over a live database to supply current market context for evaluating stocks and screening.
- What They Did
- A commenter said plain ChatGPT was not current enough and that cross-referencing metrics got messy, so they built their own RAG agent on top of a live database. They used it to add current market context for chat-based research and stock screening, but the thread does not describe the database, retrieval flow, or any human review steps.
- How It Went
- The stated outcome was better current market context for chat and screening. No performance results, accuracy numbers, or limitations beyond stale data and awkward metric cross-referencing in standard ChatGPT were given.
- Worth Knowing
- The main catch is that the source gives almost no implementation detail, so you would need to design the live database and RAG workflow yourself.
Try it yourself with custom-built or unnamed agent
Help me build a simple retrieval agent that pulls current market context for stock screening. Connect it to [data source, such as a market data API or a database I already have], index recent news and key metrics for [list of tickers or sector], and let me ask questions like 'which of these names have positive earnings revisions this week'. Done when I can run a query from the terminal and get an answer with the underlying sources shown.
Do this with a skill.
These AI Services Market playbooks do this exact job.