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[2602.13521] Arming Data Agents with Tribal Knowledge
Summary
The paper introduces Tk-Boost, a framework enhancing NL2SQL agents by integrating tribal knowledge to correct misconceptions during database querying, improving accuracy significantly.
Why It Matters
As NL2SQL agents become more prevalent in data querying, enhancing their accuracy through frameworks like Tk-Boost is crucial for non-expert users. This research addresses common errors in database interactions, making data more accessible and reliable.
Key Takeaways
- Tk-Boost improves NL2SQL agent accuracy by addressing misconceptions.
- The framework utilizes tribal knowledge accumulated from agent experiences.
- Extensive testing shows accuracy improvements of up to 16.9% on benchmarks.
Computer Science > Databases arXiv:2602.13521 (cs) [Submitted on 13 Feb 2026] Title:Arming Data Agents with Tribal Knowledge Authors:Shubham Agarwal, Asim Biswal, Sepanta Zeighami, Alvin Cheung, Joseph Gonzalez, Aditya G. Parameswaran View a PDF of the paper titled Arming Data Agents with Tribal Knowledge, by Shubham Agarwal and 5 other authors View PDF HTML (experimental) Abstract:Natural language to SQL (NL2SQL) translation enables non-expert users to query relational databases through natural language. Recently, NL2SQL agents, powered by the reasoning capabilities of Large Language Models (LLMs), have significantly advanced NL2SQL translation. Nonetheless, NL2SQL agents still make mistakes when faced with large-scale real-world databases because they lack knowledge of how to correctly leverage the underlying data (e.g., knowledge about the intent of each column) and form misconceptions about the data when querying it, leading to errors. Prior work has studied generating facts about the database to provide more context to NL2SQL agents, but such approaches simply restate database contents without addressing the agent's misconceptions. In this paper, we propose Tk-Boost, a bolt-on framework for augmenting any NL2SQL agent with tribal knowledge: knowledge that corrects the agent's misconceptions in querying the database accumulated through experience using the database. To accumulate experience, Tk-Boost first asks the NL2SQL agent to answer a few queries on the database, ...
