Spec-driven development methodology with skills for requirements, design, tasks, AI prompting, QA, and troubleshooting
Effective communication strategies for AI-assisted development. Learn context-first prompting, phased interactions, iterative refinement, and validation techniques to get better results from Claude and other AI coding assistants.
Create comprehensive steering documents for development projects. Generates project-specific standards, git workflows, and technology guidelines in .kiro/steering/ directory.
Transform approved requirements into comprehensive technical designs. Define system architecture, component interactions, data models, and interfaces to create a blueprint for implementation.
Comprehensive testing and validation strategies for spec-driven development. Learn phase-specific validation techniques, quality gates, and testing approaches to ensure high-quality implementation.
Transform vague feature ideas into clear, testable requirements using EARS format. Capture user stories, define acceptance criteria, identify edge cases, and validate completeness before moving to design.
Systematic three-phase approach to feature development using Requirements, Design, and Tasks phases. Transforms vague feature ideas into well-defined, implementable solutions that reduce ambiguity, improve quality, and enable effective AI collaboration.
Convert technical designs into actionable, sequenced implementation tasks. Create clear coding tasks that enable incremental progress, respect dependencies, and provide a roadmap for systematic feature development.
Diagnose and resolve common issues during spec-driven development and implementation. Learn strategies for handling spec-reality divergence, dependency blocks, unclear requirements, and other execution challenges.