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forge

Orchestrate AI agents to decompose user stories and manage task delivery via tmux.

Updated Dec 20, 2023
Search Tags:#testing#devops#code review#workflow automation#code generation#agent orchestration#team lead
One-click install
npx skills add https://github.com/Hakiick/ChessGame --skill forge-hakiick
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: forge
Source: https://github.com/Hakiick/ChessGame/tree/main/.claude/skills/forge
Command: npx skills add https://github.com/Hakiick/ChessGame --skill forge-hakiick

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gh, tmux, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill acts as an intelligent Team Lead, automating the complex process of breaking down user stories, delegating tasks to specialized AI agents, managing feedback loops, and ensuring stable delivery of features.

Core Features & Use Cases

  • Automated Task Decomposition: Breaks down large user stories into manageable sub-tasks.
  • Agent Orchestration: Selects and assigns tasks to the most appropriate AI agents (developer, tester, reviewer, etc.).
  • Feedback Loop Management: Facilitates iterative development by routing results and corrections between agents.
  • Quality Gates: Integrates testing, code review, and stabilization checks to ensure a high-quality output.
  • Use Case: A product manager can submit a new feature request (User Story), and the Forge skill will manage the entire development lifecycle, from initial planning and coding to testing and final delivery, reporting back on progress and any issues encountered.

Quick Start

Initiate the forge skill to begin orchestrating agent tasks for a given user story.

Frequently Asked Questions about forge

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

FAQPage Schema
How do I automate end-to-end feature delivery using AI agent orchestration?▼

AI agent orchestration automates end-to-end feature delivery by decomposing user stories into sub-tasks, delegating them to specialized agents, and managing feedback loops to ensure stable output. It acts as an automated team lead for the entire development lifecycle.

How does automated task decomposition work for breaking down user stories?▼

Automated task decomposition breaks down large user stories into manageable sub-tasks. The system then selects and assigns these specific tasks to specialized AI agents, such as developers, testers, and reviewers, to handle distinct phases of the workflow.

Do I need GitHub CLI and tmux to manage AI agent lifecycles?▼

Yes, you need GitHub CLI and tmux installed. The system requires integration with GitHub CLI for repository operations and tmux for managing agent process lifecycles and task execution within isolated terminal sessions.

Can I use workflow automation to manage feedback loops between AI agents?▼

Yes, workflow automation manages feedback loops by routing results and corrections between specialized AI agents. This iterative refinement process facilitates development cycles through defined feedback mechanisms and quality gates like testing and code review.

What are the limitations of using tmux for agent process management?▼

Using tmux for agent process management requires a Unix-like environment capable of supporting persistent terminal sessions. It is not suitable for environments lacking command-line terminal multiplexer support or where background process isolation is restricted.

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