Evaluate AI agents through five sequential phases with automated test execution.
npx skills add https://github.com/Parth576/dotfiles --skill eval-parth576
Please help me install this Agent Skill. Skill: eval Source: https://github.com/Parth576/dotfiles/tree/main/config/claude/skills/eval Command: npx skills add https://github.com/Parth576/dotfiles --skill eval-parth576
This Skill provides a structured, multi-phase framework for rigorously evaluating AI agents, ensuring comprehensive testing and evidence-based reporting.
Use the eval skill to start the evaluation process for the agent located at './my-agent'.
High-intent search queries and answers about installing and using this skill.
To evaluate AI agents systematically, this skill provides a structured testing framework through five sequential phases: planning, test data generation, execution, analysis, and documentation.
Building an automated AI evaluation pipeline involves guiding the creation of test data, implementing real agent interactions, and executing tests to generate evidence-based performance reports.
Yes, running agent testing pipelines requires a Python 3.11+ environment and an agent_path parameter to locate the target agent for test execution.
Performance analysis during AI agent testing works by executing the agent against generated test data, analyzing the results, and generating detailed reports with actionable insights and prioritized recommendations.
The documentation phase of an AI evaluation pipeline includes generating evidence-based reports that detail performance findings, actionable insights, and prioritized recommendations for agent improvements.
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