evaluation-protocol-design

Define metrics, datasets, seeds, baselines, and fairness constraints for evaluation protocols.

11|1|Updated Feb 22, 2026
One-click install
npx skills add https://github.com/EvoClaw/amplify --skill evaluation-protocol-design
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: evaluation-protocol-design
Source: https://github.com/EvoClaw/amplify/tree/main/skills/evaluation-protocol-design
Command: npx skills add https://github.com/EvoClaw/amplify --skill evaluation-protocol-design

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams design and lock a comprehensive evaluation protocol for method development projects, ensuring transparent criteria and reproducible comparisons.

Core Features & Use Cases

  • Standardizes metric selection, dataset curation, seed scheduling, and baseline listing to prevent post-hoc rationalization.
  • Guides decision gates for Type M, Type C, and Type H projects, with clear steps and justifications.
  • Enables governance and publication-ready reporting by enforcing a locked protocol document.

Quick Start

Fill in all eight protocol items and save the completed document to docs/03_plan/evaluation-protocol.yaml

Frequently Asked Questions about evaluation-protocol-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design an evaluation protocol for method development experiments?

Design an evaluation protocol by locking metrics, datasets, seeds, baselines, and fairness constraints into a standardized document. This prevents post-hoc rationalization and ensures reproducible comparisons for method development experiments.

What should be included in an evaluation protocol to ensure reproducibility?

An evaluation protocol for reproducibility must include eight design items: metrics, datasets, seeds, baselines, fairness constraints, and locked decision gates. Store the completed document as evaluation-protocol.yaml.

How do I standardize baseline selection and metric decisions across different project types?

Standardize baseline selection and metric decisions by applying locked evaluation protocols with defined decision gates for Type M, Type C, and Type H projects. This ensures consistent criteria from metric selection through baseline inclusion.

Can I use a locked evaluation protocol for publication-ready reporting?

Yes, a locked evaluation protocol enables publication-ready reporting by enforcing a locked header and all eight completed design items in the protocol document. This governance ensures transparent criteria and reproducible comparisons.

When do I need to lock an evaluation protocol for my statistics and dataset experiments?

Lock an evaluation protocol before running method development experiments to prevent post-hoc rationalization. Defining metrics, datasets, seeds, and baselines beforehand standardizes decisions and ensures reproducible statistics.