LLM Evaluation Benchmark and Regression Designer
Design LLM evaluation benchmarks with task sets, reference criteria, graders, safety cases, variability, baselines, regression gates, and reporting.
LLM Evaluation Benchmark and Regression Designer is a free AI skill for agent systems & llm workflows. Design LLM evaluation benchmarks with task sets, reference criteria, graders, safety cases, variability, baselines, regression gates, and reporting. It works with Claude, ChatGPT and is ready to use out of the box.
About this skill
Design LLM evaluation benchmarks with task sets, reference criteria, graders, safety cases, variability, baselines, regression gates, and reporting. It applies a structured workflow, labels assumptions, and produces implementation-ready guidance with ownership, controls, edge cases, and validation.
What it does
The skill analyzes goals, users, evidence, workflows, dependencies, constraints, and risks; converts them into a practical operating model; and produces explicit rules, responsibilities, exceptions, controls, tests, and rollout guidance.
What is included
- Evaluation context
- Task and risk taxonomy
- Benchmark dataset
- Expected behavior and criteria
- Grading approach
- Safety and adversarial cases
- Baselines and variability
- Regression gates
How to use it
1. Download the llm-evaluation-benchmark-and-regression-designer-SKILL.md file 2. Upload it to your AI, operational, or project workspace 3. Provide the current process, users, goals, evidence, and constraints 4. Add ownership, approval, risk, and implementation requirements 5. Use the output for design, review, testing, or rollout
Examples
Create evaluations for an AI assistant that cleans spreadsheet data, explains problems, preserves evidence, and avoids inventing results.
A complete professional deliverable with context, decisions, ownership, workflows, edge cases, risks, controls, validation criteria, and an implementation roadmap.
FAQ
What is this skill for?
Will it invent facts or results?
Can it improve an existing process?
Does it include edge cases?
Can it assign ownership?
How is this different from generic advice?
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