How to build great Claude skills for automation

TL;DR

The key is to first complete a task with Claude and then turn it into a skill, which yields better context and outcomes. Build small, focused skills for separate workflows, treat skills as living processes, and use testing in separate chats to refine without bias. Add input output examples and use progressive disclosure to manage context efficiently.

Transcript

I recently looked at Entropic's guides and best practices on cloth skills, and I found eight tips and techniques to build far more effective skills for automating work. So, in this video, I'll cover eight ways from beginning to advanced to build better skills that actually automate work reliably. If you don't know me yet, I'm Ben. I'm a three-time ... Read More

Key Insights

• The first rule is to perform the task with Claude before creating a skill, then convert the task into a skill to capture tacit knowledge.
• Build skills around single, well scoped tasks rather than packing multiple tasks into one skill for better accuracy and easier maintenance.
• Treat each skill as a living process that should be updated as edge cases arise, with separate chats for building and testing to reduce bias.
• Use a self improvement rule to automatically update the skill when you correct outputs, ensuring continual improvement.
• Include input and output examples to set the desired format and quality, guiding Claude toward the correct style and level of detail.
• Progressive disclosure ensures context is loaded only as needed, by tying reference files to specific steps rather than loading everything at once.
• Keep context windows clean by structuring skills to read only relevant references at each step, improving performance.
• Keep skills small and separate for different workflows, because small, focused skills compose better than a single large skill.

Questions & Answers

Q: How should you start building a Claude skill according to the video

Begin by performing the task with Claude in a single session to gather the actual steps, preferences, and reasoning. After achieving a successful outcome, use the turn into a skill option to convert the demonstrated process into a reusable Claude skill. This method captures practical insights that are hard to articulate from prompts alone and improves reliability.

Q: Why is it important to keep skills small and focused

Small, focused skills target a single workflow or task, reducing complexity and context drift. This makes it easier to iterate, test, and improve the skill, and allows multiple smaller skills to compose into a complete workflow more reliably than one large, universal skill.

Q: What does it mean to treat a skill like a business process

Skills should be maintained and updated as the business environment changes, much like living processes. They should be refined over time with edge cases added and improvements implemented, rather than being treated as static outputs. This approach yields more robust and adaptable automation.

Q: How should you test Claude skills to avoid bias

Use one chat dedicated to building and refining the skill, and a separate chat to test it on real workflows. If the skill makes mistakes, provide corrections in the test chat and then update the skill accordingly, ensuring testing remains unbiased and focused on performance.

Q: What is the role of a self improvement rule in skills

A self improvement rule automatically captures corrections or desirable outputs and updates the skill with new rules or examples. This creates a feedback loop where better results are consistently integrated into the skill, improving reliability over time.

Q: Why are input and output examples important for skills

Examples demonstrate the desired style, level of detail, and format, guiding Claude to produce outputs that match expectations. They are especially valuable for design, copy, or creative workflows where precise tone and structure matter.

Q: What is progressive disclosure in the context of Claude skills

Progressive disclosure means loading references and context only when needed for a given step, rather than exposing all context at the start. This prevents context overload and maintains performance while still providing rich information when required.

Q: How should reference files be used for better performance

Reference files should be attached to specific steps or tasks so Claude reads only what is necessary at each stage. This targeted use of context preserves the most relevant information for downstream steps and avoids polluting the context window with unnecessary data.

Summary & Key Takeaways

• This video emphasizes turning tasks into Claude skills only after actually performing the task, which improves guidance and reliability. It argues for small, focused skills rather than one large, broad skill to keep context windows clean and performance high. It also encourages iterative refinement, testing separately, and treating skills as evolving business processes.

• A core principle is to use the show dont tell approach, documenting outputs with examples for better tone and detail control. The speaker recommends a self improvement rule to automatically save good outputs and feed them back into the skill. Progressive disclosure helps manage context by loading references only when needed.

• The content also covers practical steps like adding input/output examples, maintaining separate chats for building and testing, and using reference files strategically to avoid context overload, thereby enhancing scalability and adaptability of Claude workflows.