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Skill Context Window

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Description

This MicroSim visualizes the progressive disclosure design principle used in Claude Skills. Skills use a three-level loading system to manage context efficiently and avoid overwhelming Claude's context window.

The Three Layers

Hover over each layer to see detailed information about when and how it's loaded:

  1. SKILL.md Frontmatter (Top - Always Loaded ~100 words)

  2. Contains skill name and description

  3. Always in context when Claude starts
  4. Allows Claude to decide when to invoke the skill

  5. Minimal token usage

  6. SKILL.md File (Middle - When Triggered <5k words)

  7. Complete skill instructions and workflows

  8. Loaded when the skill is triggered/invoked
  9. Contains procedural knowledge and examples

  10. Moderate token usage

  11. Assets, References, Templates & Scripts (Base - As Needed, Unlimited)

  12. Scripts can be executed without loading into context

  13. References loaded when Claude determines they're needed
  14. Templates and assets used in output
  15. Provides unlimited extensibility

Progressive Disclosure Benefits

This layered approach provides several key advantages:

  • Efficiency: Only loads what's needed, when it's needed
  • Scalability: Skills can have unlimited resources without context bloat
  • Performance: Minimal startup cost with full capability available
  • Flexibility: Claude intelligently loads additional resources on demand

Visual Design

The triangle shape represents the progressive expansion of context: - Narrow top: Minimal frontmatter (always present) - Medium middle: Full skill file (when active) - Wide base: Extensive resources (loaded selectively)

The color coding indicates loading behavior: - Yellow: Always in context (startup) - Blue: Loaded when skill triggers (on-demand) - Green: Loaded as needed (selective)

Lesson Plan

Target Audience: Developers creating Claude Skills, AI prompt engineers, educational technologists

Learning Objectives:

By the end of this lesson, students will be able to:

  1. Understand the three-level progressive disclosure system in Claude Skills
  2. Explain when each layer is loaded into Claude's context window
  3. Design efficient skills that minimize context usage
  4. Apply progressive disclosure principles to their own skill development
  5. Recognize the benefits of layered architecture for AI agent systems

Prerequisites:

  • Basic understanding of Claude and AI language models
  • Familiarity with context windows and token limits
  • Knowledge of skills or similar modular systems

Duration: 15-20 minutes

Activities:

  1. Introduction (3 minutes)
  2. Explain the challenge of context window management
  3. Introduce progressive disclosure as a solution

  4. Show the MicroSim

  5. Exploration Activity (7 minutes)

  6. Students hover over each layer to read the details
  7. Discuss the size differences (~100 words vs <5k words vs unlimited)

  8. Compare loading strategies (always vs triggered vs as-needed)

  9. Analysis Exercise (5 minutes)

  10. Question: "Why is the frontmatter always loaded while assets are loaded as needed?"
  11. Discuss trade-offs between context usage and capability

  12. Analyze real skill examples

  13. Application Activity (5 minutes)

  14. Design a hypothetical skill using the three-layer model
  15. Decide what goes in each layer
  16. Justify the placement decisions

Assessment:

  • Formative: Monitor discussions during exploration
  • Summative: Have students design a skill architecture
  • Extended: Create an actual skill following the progressive disclosure pattern

Extensions:

  • Compare progressive disclosure to other architectural patterns (monolithic, microservices)
  • Explore how other AI systems manage context windows
  • Investigate token economics and context optimization strategies

Skill Design Principles

This MicroSim illustrates key principles from the skill-creator documentation:

Progressive Disclosure

Definition: A three-level loading system that manages what information is in Claude's context at different stages.

Levels: 1. Metadata (name + description) - Always in context (~100 words) 2. SKILL.md body - When skill triggers (<5k words) 3. Bundled resources - As needed by Claude (unlimited*)

*Unlimited because scripts can be executed without reading into context window.

Context Efficiency

Why it matters: Claude's context window is finite. Loading everything upfront would: - Waste tokens on unused information - Slow down processing - Reduce capacity for actual task work - Limit skill complexity

How progressive disclosure helps: - Minimal startup cost (just metadata) - Full capability available when needed - Selective resource loading - Unlimited potential complexity

Resource Organization

Scripts (scripts/): - Executed without loading into context - Provide deterministic operations - Example: Screenshot capture, file manipulation

References (references/): - Loaded into context when Claude needs them - Provide detailed documentation - Example: API specs, schemas, detailed guides

Assets (assets/): - Used in output, not loaded into context - Provide templates and resources - Example: Templates, boilerplate, images

Technical Implementation

Architecture: Based on the knowledge-triangle MicroSim pattern - Responsive canvas design (width-responsive) - Three-layer triangle visualization - Interactive hover detection - Informative popup boxes

Key Features: - Clean, text-only layers (no background objects) - Color-coded loading strategies - Context-sensitive hover information - Professional educational design

p5.js Techniques: - Triangle geometry calculations - Point-in-polygon detection - Dynamic text wrapping - Responsive canvas sizing

References

  1. Claude Skills Documentation - Official documentation for Claude Code skills
  2. Skill Creator Skill - The skill that creates other skills, demonstrates progressive disclosure
  3. Progressive Disclosure (Nielsen Norman Group) - 2006 - UX design pattern for managing complexity
  4. Context Window Management in LLMs - 2023 - Anthropic - Technical background on context windows
  5. Modular Design Patterns - Wikipedia - Software architecture patterns for managing complexity