Evaluate and refine agent outputs through structured reflection loops.
npx skills add https://github.com/yiwei79/azoth --skill agentic-eval-yiwei79
Please help me install this Agent Skill. Skill: agentic-eval Source: https://github.com/yiwei79/azoth/tree/main/.opencode/skills/agentic-eval Command: npx skills add https://github.com/yiwei79/azoth --skill agentic-eval-yiwei79
Agent outputs are often inconsistent and require manual review. This Skill provides structured evaluation patterns and loops to autonomously critique and refine results, improving reliability and alignment with goals.
Initiate a reflection loop on a given agent output and iteratively revise it until all criteria are satisfied.
High-intent search queries and answers about installing and using this skill.
You can refine agent outputs by applying an evaluator-optimizer pattern, which separates generation and evaluation into distinct components. This drives iterative improvement cycles until all quality criteria and guardrails are satisfied.
Yes, structured evaluation integrates with evaluator pipelines using the agentic-eval patterns. It provides structured JSON results, enforcing guardrails and enabling autonomous critique and refinement within existing automation workflows.
The evaluator-optimizer pattern separates generation and evaluation into distinct components. This separation drives iterative improvement by allowing the evaluator to independently critique the generator's output until criteria are met.
To start a reflection loop, initiate the process on a given agent output and iteratively revise it. The agent evaluates and refines its own output through self-critique until all specified criteria are satisfied.
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