moai-workflow-research

Coordinate moai-adk research workflows through iterative binary evaluation experiments.

Updated Mar 25, 2026

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

Ready to run

npx skills add https://github.com/taewook486/anki_rag --skill moai-workflow-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: moai-workflow-research
Source: https://github.com/taewook486/anki_rag/tree/main/.claude/skills/moai-workflow-research
Command: npx skills add https://github.com/taewook486/anki_rag --skill moai-workflow-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a structured, repeatable methodology to optimize moai-adk components (skills, agents, rules, config) via iterative binary evaluations, reducing ad-hoc experimentation and human drift.

Core Features & Use Cases

Iterative binary evaluation experiments to compare configurations and component changes (skills, agents, rules, config).
Built-in 5-layer safety architecture, risk controls, and worktree sandboxing to ensure safe experimentation.
Data location conventions for eval suites, baselines, experiments, and observations to support reproducible research lifecycle.
Eval-suite schema definitions and a lightweight dashboard workflow to track status, results, and progress.

Quick Start

Initialize a new moai-adk workflow research session and start the first evaluation cycle.

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 moai-adk research workflows for reproducible experimentation?▼

Automate moai-adk research workflows by coordinating end-to-end iterative binary evaluation experiments across isolated worktrees, ensuring reproducible pipelines for skills, agents, rules, and config components.

What is the best way to evaluate moai-adk component changes safely?▼

Evaluate moai-adk component changes safely using a built-in five-layer safety architecture, risk controls, and worktree sandboxing to isolate experiments and prevent human drift during ad-hoc testing.

How do I track progress and results for moai-adk evaluation suites?▼

Track moai-adk evaluation suite progress and results using defined schema definitions and a lightweight dashboard workflow that monitors status, observations, and experiment lifecycles.

Can I use this workflow to compare different moai-adk agent configurations?▼

Yes, you can use this workflow to compare moai-adk agent configurations through iterative binary evaluations, applying data location conventions for baselines and observations to support reproducible research.

Do I need isolated worktrees to run moai-adk research pipelines?▼

Yes, isolated worktrees are required to run moai-adk research pipelines, providing a sandboxed environment that satisfies the five-layer safety architecture and ensures safe experimentation.

Why does my moai-adk research workflow suffer from configuration drift?▼

Moai-adk research workflows suffer from configuration drift due to ad-hoc experimentation, which this structured methodology reduces by enforcing data location conventions and reproducible binary evaluation cycles.