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claudecraft

Orchestrate a spec-driven software development lifecycle with AI agents.

11|2|Updated Feb 26, 2026
Search Tags:#automation#workflow#development#claude#agent#spec#tui
One-click install
npx skills add https://github.com/ivo-toby/talon --skill claudecraft-ivo-toby
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: claudecraft
Source: https://github.com/ivo-toby/talon/tree/main/.claude/skills/claudecraft
Command: npx skills add https://github.com/ivo-toby/talon --skill claudecraft-ivo-toby

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the entire software development lifecycle, from initial idea to autonomous implementation, by providing a structured, spec-driven workflow.

Core Features & Use Cases

  • End-to-End Workflow: Manages the process from Business Requirements Documents (BRDs) to final Quality Assurance (QA).
  • Autonomous Execution: Automates planning, task decomposition, implementation, and testing using AI agents.
  • Use Case: Kickstart a new project by defining requirements, generating a technical specification, and then having AI agents autonomously write, test, and validate the code.

Quick Start

Initialize a new ClaudeCraft project using the claudecraft.init command.

Frequently Asked Questions about claudecraft

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

FAQPage Schema
What is spec-driven development and how does an AI agent orchestrate it?▼

Spec-driven development manages the software lifecycle from idea generation through BRD, PRD, specification, and QA. AI agents orchestrate this by autonomously planning, decomposing tasks, implementing, and testing code based on defined specifications.

How do I automate software development workflows from requirements to QA?▼

Automate software development workflows by initializing a spec-driven orchestrator to generate technical specifications from requirements, allowing AI agents to autonomously write, test, and validate code through to final QA.

Can I run parallel AI agents for code implementation with Git worktree isolation?▼

Yes, spec-driven development orchestrators support parallel agent execution with Git worktree isolation, enabling multiple autonomous implementation tasks to run concurrently without interfering with each other's codebase.

How do I track real-time progress of autonomous AI coding agents?▼

Track real-time progress of autonomous AI coding agents via a TUI, providing live updates as agents execute planning, implementation, and testing phases within the software development lifecycle.

Does spec-driven development work for generating technical specifications from business requirements?▼

Yes, spec-driven development manages the workflow from Business Requirements Documents (BRDs) and Product Requirements Documents (PRDs) to generate detailed technical specifications for autonomous implementation.

What are the limitations of using autonomous AI agents for software implementation?▼

Autonomous AI agents require structured specifications to function effectively; without clear BRDs, PRDs, and technical specs, the automated planning, implementation, and QA validation may produce misaligned code.

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