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This release introduces a rigorous, open-source framework for evaluating AI coding agents on real-world database and security tasks within the Supabase ecosystem. By utilizing deterministic checks alongside LLM-as-a-judge scoring against actual schemas and RLS policies, it establishes a new standard for regression testing agent capabilities in production environments. The tool effectively bridges the gap between theoretical benchmarking scores and practical deployment reliability for developer tools.
Supabase Releases Evals: an Open Source Benchmark That Scores Claude Code, Codex and OpenCode on Real Supabase Tasks
Supabase has open sourced supabase/evals, an Apache-2.0 benchmark and framework that runs coding agents including Claude Code, Codex and OpenCode against real Supabase tasks — building schemas, debugging Edge Functions, fixing RLS policies — inside containerized stacks, then scores them with deterministic checks and LLM-as-a-judge. The post Supabase Releases Evals: an Open Source Benchmark That Scores Claude Code, Codex and OpenCode on Real Supabase Tasks appeared first on MarkTechPost.
Supabase has open sourced Supabase Evals, its benchmark and framework for testing how well AI agents build using Supabase. It runs coding agents including Claude Code, Codex, and OpenCode against real tasks, such as building a schema, debugging a failed Edge Function, or fixing a broken RLS policy, then scores the…
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