Supabase implemented a framework to evaluate their documentation's effectiveness for AI coding agents by running automated agent-based tests against technical guides. By comparing agent outcomes against an independent checklist of security requirements rather than the documentation itself, the team identified structural improvements that benefit both AI agents and human developers. The findings suggest that clear, explicit technical writing remains the most effective strategy for ensuring both human comprehension and reliable agent execution.
Key points
Evaluating documentation for AI agents requires checklists based on independent requirements rather than the text of the guide itself.
Documentation that is structured, explicit, and signposted effectively serves both human readers and AI coding agents.
Automated evaluation frameworks help identify 'silent failures' in documentation, such as missing configuration steps or prerequisites.
Testing documentation against AI agents should be an iterative process integrated into the development lifecycle.
