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EvalTrim
Local-first evaluation control plane for AI agents that detects redundant evals, regressions, unique behavioral witnesse
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https://github.com/lowjieseng1810/evaltrim
About EvalTrim
EvalTrim is a local-first evaluation control plane for AI agents. It helps developers run and compare evaluations, detect regressions, identify redundant tests and unique behavioral witnesses, simulate test removal, and maintain smaller, safer evaluation suites. Instead of only asking whether an agent passed, EvalTrim also asks which tests actually contribute unique behavioral coverage. Key capabilities include: - redundant and near-duplicate eval detection - unique behavioral witness detection - counterfactual test-removal simulation - regression and drift analysis - flaky and conflicting evaluation detection - suite health and evaluation debt - evidence-backed maintenance recommendations - GitHub Actions integration EvalTrim runs locally by default, uses no hosted backend, and never silently deletes tests. Recommendations remain reviewable and are backed by structured evidence.
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