💡 Summary
Kiro provides a structured approach to spec-driven development, enhancing collaboration and efficiency in feature development.
🎯 Target Audience
🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); dependency pinning and supply-chain risk. Run with least privilege and audit before enabling in production.
Spec-Driven Development Guide
A comprehensive guide to systematic feature development using the three-phase spec process: Requirements → Design → Tasks.
Used by
- @kazini in their spec kit https://github.com/kazini/yask-spec-kit
- Amazon in internal presentations: "It’s the best stuff I have found on [spec driven development]. I will be sharing links back to your repo with full attribution."
🧭 Navigation Guide
New to spec-driven development? → Start with Methodology Overview
Ready to create your first spec? → Jump to Process Guide
Looking for examples? → Browse Examples & Case Studies
Need templates? → Get Ready-to-Use Templates
Working with AI? → Learn Prompting Strategies
📍 Need detailed navigation? → See Complete Navigation Index - Find content by role, problem, or learning style
📚 Complete Table of Contents
🎯 Methodology
Learn the foundational concepts and philosophy behind spec-driven development
- Overview - Core concepts and benefits
- Philosophy - Why spec-driven development works
- When to Use - Decision framework and scenarios
📋 Process Guide
Step-by-step walkthrough of the three-phase workflow
- Requirements Phase - Gathering and structuring requirements using EARS
- Design Phase - Creating comprehensive design documents
- Tasks Phase - Breaking down design into actionable coding tasks
- Workflow Diagrams - Visual process flows and decision points
🧠 AI Reasoning
Insights into decision-making frameworks and thought processes
- Decision Frameworks - How choices are evaluated
- Thought Processes - Analysis and prioritization methods
- Examples - Real reasoning chains and decision points
💬 Prompting Strategies
Effective communication techniques for AI collaboration
- Strategies - Core prompting approaches
- Templates - Ready-to-use prompt patterns
- Best Practices - Tips for clear, effective communication
⚡ Execution Guide
Practical guidance for implementing features from specs
- Implementation Guide - Step-by-step execution strategies
- Quality Assurance - Testing and validation techniques
- Troubleshooting - Common issues and solutions
📚 Resources
Curated references and learning materials
- Standards - EARS and industry standards
- Tools - Recommended tools and integrations
- Further Reading - Additional learning resources
📖 Examples
Real-world case studies and complete spec examples
- Simple Feature Specs - Basic feature examples
- Complex System Specs - Large system examples
- Case Studies - Success stories and lessons learned
- Troubleshooting & Pitfalls - Common mistakes and recovery strategies
📝 Templates
Ready-to-use templates and checklists
- Requirements Template - EARS-formatted requirements
- Design Template - Comprehensive design structure
- Tasks Template - Implementation planning format
Quick Start
New to spec-driven development? Start here:
- Understand the Methodology - Read the Overview to grasp core concepts
- See It in Action - Review a Simple Feature Spec example
- Try It Yourself - Use the Requirements Template for your first spec
- Get Better Results - Apply Prompting Strategies for AI collaboration
Navigation Tips
- 📋 Process sections provide step-by-step instructions
- 🧠 AI Reasoning sections explain the "why" behind decisions
- 💬 Prompting sections help you communicate effectively with AI
- 📖 Examples show complete, real-world applications
- 📝 Templates give you ready-to-use starting points
🔗 Cross-References & Related Content
By Workflow Phase
- Planning Phase: Methodology → Requirements → Design → Tasks
- Execution Phase: Implementation Guide → Quality Assurance
- AI Collaboration: Prompting Strategies → AI Reasoning → Best Practices
By Experience Level
- Beginner: Methodology → Simple Examples → Templates
- Intermediate: Process Guide → Prompting Strategies → Case Studies
- Advanced: AI Reasoning → Complex Examples → Decision Frameworks
Quick Problem Solving
- Unclear Requirements → Requirements Phase + EARS Standards
- Design Challenges → Design Phase + AI Decision Frameworks
- Implementation Issues → Implementation Guide + Troubleshooting
- AI Communication Problems → Prompting Best Practices + Troubleshooting
🔌 Kiro MCP Server
The Kiro MCP Server exposes Kiro's system prompts and instructions through the Model Context Protocol (MCP), allowing other AI assistants and tools to access Kiro's best practices.
Features
- Resources: Access all Kiro system documentation files via MCP resources
- Tools: Query and retrieve specific system instructions programmatically
- Prompts: Pre-configured prompts for common Kiro workflows
Quick Start
Install and configure the MCP server:
# Using uvx (recommended) uvx kiro-mcp-server # Or install with pip pip install kiro-mcp-server
Add to your MCP client configuration (e.g., ~/.kiro/settings/mcp.json):
{ "mcpServers": { "kiro-prompts": { "command": "uvx", "args": ["kiro-mcp-server"], "disabled": false } } }
For more details, see the MCP Server Documentation.
🎯 Claude Code Plugin
Kiro is available as an installable Claude Code plugin with 7 skills following the agentskills.io specification.
Quick Install
# In Claude Code /plugin marketplace add https://github.com/jasonkneen/kiro /plugin install kiro-spec-driven@kiro-marketplace
Available Skills
Once installed, Claude automatically uses these skills when relevant:
| Skill | Description | Use When | |-------|-------------|----------| | spec-driven-development | Master methodology | "create a spec for..." | | requirements-engineering | EARS format | "write requirements for..." | | design-documentation | Technical architecture | "design the architecture..." | | task-breakdown | Implementa
Pros
- Comprehensive methodology for feature development.
- Promotes collaboration between AI and human teams.
- Includes templates and examples for practical use.
Cons
- May overwhelm beginners with extensive content.
- Requires familiarity with AI collaboration concepts.
- Dependency on external tools for full functionality.
Related Skills
claude-mods
A“Powerful, but the setup might scare off the impatient.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author jasonkneen.
