moai-workflow-research

Optimize Moai-ADK components through iterative binary-eval experiments against baselines.

Updated Apr 19, 2026

Search Tags:#workflow #research #evaluation #safety #experimentation #baselines #moai-adk

Ready to run

npx skills add https://github.com/windysky/snake-game --skill moai-workflow-research-windysky

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: moai-workflow-research
Source: https://github.com/windysky/snake-game/tree/main/.claude/skills/moai-workflow-research
Command: npx skills add https://github.com/windysky/snake-game --skill moai-workflow-research-windysky

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This workflow enables systematic optimization of Moai-ADK components through iterative binary-eval experimentation loops with built-in safeguards to prevent unsafe changes.

Core Features & Use Cases

Isolated evaluation framework: Organizes eval suites, baselines, experiments, and changelogs to compare new changes against proven baselines.
Safety-first governance: Implements a five-layer safety architecture (FrozenGuard, worktree sandbox, canary regression, rate limiting, human approval) to guard experiments.
Continuous improvement: Supports repeatable experiments for skills, agents, rules, and configs, with structured observations and dashboards.

Quick Start

Run an isolated research cycle to test a new Moai-ADK component against the baseline and review the results.

Frequently Asked Questions about moai-workflow-research

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

FAQPage Schema

How do I automate workflow research experiments against established baselines?▼

Automate workflow research experiments by running iterative binary-eval tests that compare new components against proven baselines. The system organizes eval suites and changelogs, applying your evaluation schema to systematically identify optimization opportunities.

What is a binary-eval experimentation loop for agent and skill optimization?▼

A binary-eval experimentation loop iteratively tests new skills, agents, rules, or configs against a baseline to measure pass or fail outcomes. It organizes observations across isolation worktrees to validate component changes before integration.

How do I ensure safety when testing experimental agent configurations?▼

Ensure safety during experimentation by using a five-layer architecture that includes FrozenGuard, worktree sandboxes, canary regressions, rate limiting, and human approval. These safeguards prevent unsafe modifications from affecting baseline workflows.

Do I need a specific evaluation schema to run Moai-ADK experiments?▼

Yes, you need a defined evaluation schema specifying runs_per_experiment, max_experiments, and a pass/fail threshold. You must also provide data locations for eval suites, baselines, experiments, and observations to execute the research workflow.

What is the best way to organize isolated research cycles for workflow components?▼

Organize isolated research cycles by separating eval suites, baselines, experiments, and changelogs into distinct worktrees. This isolation lets you test Moai-ADK components systematically and review results on dashboards without risking the baseline.