Skills

Complete alphabetical index of all skills available across Context Engineering Kit plugins.

Skills by Plugin

Test-Driven Development (TDD)

Testing-first development methodology with Red-Green-Refactor cycle. More info.

  • test-driven-development - Introduces TDD methodology, best practices, and skills for testing using subagents.

Subagent-Driven Development (SADD)

Multi-agent task orchestration with quality gates between tasks. More info.

  • subagent-driven-development - Dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates.

  • multi-agent-patterns - Design multi-agent architectures (supervisor/orchestrator, peer-to-peer/swarm, hierarchical) for complex tasks exceeding single-agent context limits.

Domain-Driven Development (DDD)

Architecture and design principles for maintainable software. More info.

  • software-architecture - Includes Clean Architecture, SOLID principles, and other design patterns.

Kaizen

Continuous improvement methodology with multiple analysis techniques. More info.

  • kaizen - Japanese continuous improvement philosophy with root cause analysis, Five Whys, PDCA cycles, and lean practices.

Git

Streamlined Git operations with advanced workflow patterns. More info.

  • worktrees - Use when working on multiple branches simultaneously, context switching without stashing, reviewing PRs while developing, testing in isolation, or comparing implementations across branches.

  • notes - Use when adding metadata to commits without changing history, tracking review status, test results, code quality annotations, or supplementing commit messages post-hoc.

Customaize Agent

Prompt engineering techniques and patterns for creating effective extensions. More info.

  • prompt-engineering - Well-known prompt engineering techniques and patterns, includes Anthropic Best Practices and Agent Persuasion Principles.

  • context-engineering - Deep understanding of context mechanics in agent systems: attention budget, progressive disclosure, lost-in-middle effect, and practical optimization patterns.

  • agent-evaluation - Evaluation frameworks for agent systems including LLM-as-Judge techniques, multi-dimensional rubrics, bias mitigation, and the 95% performance finding.

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