Generate code, grade with multiple evaluators, and compile reports for AI prompts.
npx skills add https://github.com/ronniegeraghty/hyoka --skill eval-pipeline
Please help me install this Agent Skill. Skill: eval-pipeline Source: https://github.com/ronniegeraghty/hyoka/tree/main/.agents/skills/eval-pipeline Command: npx skills add https://github.com/ronniegeraghty/hyoka --skill eval-pipeline
The eval pipeline provides a structured, end-to-end workflow to generate, grade, review, and report on AI-agent prompts, enabling consistent evaluation and faster debugging of prompts and agents.
Run an evaluation pipeline that generates code, grades it using multiple graders, and compiles a final report for a selected prompt.
High-intent search queries and answers about installing and using this skill.
An end-to-end evaluation pipeline orchestrates code generation, multi-model grading, and report compilation for AI agent prompts. It assesses quality, safety, and guideline adherence while capturing action timelines and isolating workspaces to ensure reproducible pass/fail experiment tracking.
Multi-model grading evaluates AI agent prompts using multiple evaluators to assess generation quality, safety, and adherence. The pipeline applies these graders in parallel with configurable limits, compiling their feedback into a comprehensive pass/fail report for faster debugging.
Yes, the evaluation pipeline assesses both safety and adherence of generated code. It applies multiple evaluators across diverse services to grade outputs, capturing detailed action timelines to audit how well AI agents follow guidelines and safety considerations.
To ensure reproducible AI agent evaluation, the pipeline implements workspace isolation and captures detailed action timelines. This structured approach guarantees that generation, grading, and reporting steps are tracked consistently across experiments for reliable debugging.
The best way to debug AI agent prompts is using an automated pipeline that generates code, applies multiple graders, and compiles a comprehensive report. This structured workflow identifies strengths and weaknesses across quality and safety, enabling faster debugging.
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