mckinsey / ark-architecture
Install for your project team
Run this command in your project directory to install the skill for your entire team:
mkdir -p .claude/skills/ark-architecture && curl -L -o skill.zip "https://fastmcp.me/Skills/Download/2909" && unzip -o skill.zip -d .claude/skills/ark-architecture && rm skill.zip
Project Skills
This skill will be saved in .claude/skills/ark-architecture/ and checked into git. All team members will have access to it automatically.
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Design architecture for Ark features following existing patterns and principles. Use when planning new features, extending components, or evaluating technical approaches.
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Skill Content
--- name: ark-architecture description: Design architecture for Ark features following existing patterns and principles. Use when planning new features, extending components, or evaluating technical approaches. --- # Ark Architecture Skill Design architecture for Ark features following existing patterns and principles. ## Process 1. **Analyze Current Solution** - Use the ark-analysis skill to examine relevant parts of the codebase 2. **Identify Patterns** - Find existing idioms, data models, and service structures to reuse 3. **Design for Reuse** - Extend existing components rather than creating new ones 4. **Enable Incremental Updates** - Break changes into small, independent pieces 5. **Flag One-Way Decisions** - Raise questions on choices that are hard to reverse ## Principles - **Reuse over creation** - Extend existing services, models, and patterns - **Follow existing idioms** - Match current code style, naming, and structure - **Incremental delivery** - Design so features can be shipped in stages - **Reversibility** - Identify and question decisions that lock in future options ## Conventions - **Watch endpoints**: Use `?watch=true` query param for SSE streaming (Kubernetes-style) - **Service ports**: Use named ports (e.g., `port: mcp`) rather than port numbers ## Output Architecture documents should include: - Component diagram showing how new pieces fit with existing ones - Data model extending current schemas - API design following existing conventions - List of one-way decisions requiring team input - Implementation phases for incremental delivery