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How to Design and Visualize AI Evals Using Open Source Frameworks

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Developers testing AI tools like agent skills or MCP servers often lack a reliable way to measure whether those tools justify the token and time costs involved. Open source evaluation frameworks such as Inspect AI and Harbor can be used to benchmark agent skills in an isolated Docker environment. A practical demo series shows how to run these evaluations using multiple Gemini models, separating solver and grader roles to reduce quota consumption. A decoupled grader architecture with binary rubric decisions is used to deliver consistent results without relying on the most expensive models. The series also covers extending evaluations by visualizing trends and collaboratively analyzing results through Google Sheets and Data Studio.

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How to Design and Visualize AI Evals Using Open Source Frameworks · ShortSingh