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Part 2 of a 5-part series on building production-grade skills for Claude Previous: Part 1: What Are Claude Skills | Next: Part 3: Building Your First Skill A skill is simply a folder with no special tooling, no compilation step, and no package manager required, yet the structure of that folder and the precision of its metadata determine whether Claude uses your skill effectively or ignores it entirely. File Structure your-skill-name/ ├── SKILL.md # Required: main instruction file ├── scripts/ # Optional: executable code │ ├── process_data.py │ └── validate.sh ├── references/ # Optional: documentation loaded as needed │ ├── api-guide.md │ └── examples/ └── assets/ # Optional: templates, fonts, icons └── report-template.md Critical naming rules: ...

Part 3 of a 5-part series on building production-grade skills for Claude Previous: Part 2: Anatomy of a Skill | Next: Part 4: Skill Patterns That Work The most effective skill creators start by doing the task manually with Claude, iterating until it works, and then extracting the winning approach into a skill rather than beginning with YAML. This part walks through that process. Step 1: Start With Use Cases, Not Code Before writing anything, identify 2 to 3 concrete use cases. A well-defined use case looks like this: ...

Part 4 of a 5-part series on building production-grade skills for Claude Previous: Part 3: Building Your First Skill | Next: Part 5: Testing, Debugging, and Distributing These patterns emerged from skills built by early adopters and Anthropic’s internal teams, and they represent common approaches that work well rather than prescriptive templates. Pick the one that matches your use case. Problem-First vs. Tool-First Before choosing a pattern, decide your framing: Problem-first: “I need to set up a project workspace” → Your skill orchestrates the right MCP (Model Context Protocol) calls in sequence, where users describe outcomes and the skill handles tools. Tool-first: “I have Notion MCP connected” → Your skill teaches Claude optimal workflows and best practices, where users have tool access and the skill provides expertise. Most skills lean one direction, and knowing which one helps you pick the right pattern. ...

Part 5 of a 5-part series on building production-grade skills for Claude Previous: Part 4: Skill Patterns That Work A skill that works in your head but breaks in production remains a draft until you validate it. This final part covers how to validate, debug, and ship your skills to users. Testing Approaches by Rigor Choose based on your audience: Approach Best For Setup Required Manual testing in Claude.ai Personal skills, rapid iteration None Scripted testing in Claude Code Team skills, repeatable validation Minimal Programmatic testing via Skills API Enterprise skills, CI/CD (Continuous Integration/Continuous Deployment) integration Moderate A skill used internally by a small team has different testing needs than one deployed to thousands of enterprise users. Match your rigor to your risk. ...

Part 1 of a 5-part series on building production-grade skills for Claude Next: Part 2: Anatomy of a Skill If you’ve ever caught yourself re-explaining the same workflow to Claude (your team’s code review process, your document formatting standards, your data pipeline methodology), skills solve that problem permanently by letting you teach Claude once so it applies that knowledge every time. A skill is a folder containing instructions, packaged as Markdown with YAML frontmatter, that teaches Claude how to handle specific tasks or workflows. Think of it as encoding your domain expertise into a reusable, portable unit that Claude loads on demand. ...

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