zenigame-improve-cycle

Orchestrate Alpha Factory improvement cycles across analysis, planning, implementation, execution, and reporting.

Updated Apr 17, 2026

Search Tags:#automation #workflow #design #planning #orchestrate #alpha-factory

Ready to run

npx skills add https://github.com/kent013/zenigame-fx --skill zenigame-improve-cycle

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: zenigame-improve-cycle
Source: https://github.com/kent013/zenigame-fx/tree/main/.claude/skills/_archived/zenigame-improve-cycle
Command: npx skills add https://github.com/kent013/zenigame-fx --skill zenigame-improve-cycle

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the coordination of the Alpha Factory improvement cycle by unifying analysis, planning, implementation, execution, and reporting into a repeatable workflow.

Core Features & Use Cases

End-to-end orchestration of analyze-run → plan-and-design → implement → run → report phases across runs.
Flexible run modes such as --repeat, --observe-only, --skip-todo, and --skip-consensus to control automation and governance.
Built-in state management and documentation hooks using devnotes and a current-cycle state file to enable resumption after interruptions.

Quick Start

Initiate a cycle by running the command /zenigame-improve-cycle to start the automated improvement loop.

Frequently Asked Questions about zenigame-improve-cycle

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

FAQPage Schema

How do I automate an end-to-end Alpha Factory improvement cycle?▼

To automate an Alpha Factory improvement cycle, you orchestrate the analyze, plan, implement, execute, and report phases into a single repeatable workflow. Running the command initiates the automated loop, coordinating state tracking and phase progression automatically.

What is an automated improvement cycle workflow in data science teams?▼

An automated improvement cycle workflow coordinates analysis, planning, implementation, execution, and reporting across runs. It enables data science teams to establish repeatable cycles for analyzing results, designing improvements, running experiments, and generating reports without manual handoffs.

Can I run the improvement cycle in observe-only mode or skip consensus?▼

Yes, you can run the improvement cycle in observe-only mode or skip consensus. The orchestration supports flexible run modes including --repeat, --observe-only, --skip-todo, and --skip-consensus to control automation levels and governance across workflow phases.

How does the workflow handle interruptions during an improvement cycle?▼

The workflow handles interruptions using built-in state management and documentation hooks. It tracks the current-cycle state using devnotes and a state file, enabling the automated orchestration to resume the improvement loop seamlessly after unexpected stops.

Does the orchestration workflow support integration with Codex and Zenigame?▼

Yes, the orchestration workflow supports integration with Codex and Zenigame. It coordinates end-to-end Alpha Factory improvement cycles by satisfying requirements for phase progression, state tracking, emergency handling, and integration with these existing workflows.