Evaluate AI agents using code, model, and human graders.
npx skills add https://github.com/GratefulJinx77/tai --skill evals-gratefuljinx77
Please help me install this Agent Skill. Skill: evals Source: https://github.com/GratefulJinx77/tai/tree/main/.tai/skills/utilities/Evals Command: npx skills add https://github.com/GratefulJinx77/tai --skill evals-gratefuljinx77
This Skill provides a comprehensive framework for evaluating AI agents across various domains, ensuring they meet specific quality and performance standards.
Run the evals skill with the specific use case and test cases to evaluate the performance of an AI agent.
High-intent search queries and answers about installing and using this skill.
AI agent regression testing requires configuring specific test cases, prompts, and graders. This framework uses code-based, model-based, and human graders to evaluate whether agents maintain performance standards across updates.
Objective AI agent benchmarking applies code, model, and human graders to measure performance against customizable test cases. This approach ensures agents meet specific quality standards by scoring outputs across various domains.
Yes, agent evaluation supports a multi-grader system combining code-based, model-based, and human graders. This allows thorough evaluation by applying different scoring criteria to the same test cases and prompts.
AI capability testing setup requires defining test cases, prompts, and grading criteria in formats like yaml or json. The framework processes these configurations to run scalable evaluations and measure agent capabilities.
Sqlite is used as a dependency for performance measurement of AI agents. It supports the scalable evaluation framework by storing test configurations and scoring results for large-scale agent benchmarking.
The multi-grader system for agent benchmarking requires careful configuration of test cases and scoring criteria. While it supports code, model, and human graders, human grading can limit scalability compared to automated evaluation methods.
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bmsull560Evaluate agent performance and extraction accuracy in LangGraph pipelines.
Clean1inesEvaluate Claude Code sessions with configurable graders and run pipelines.
