Table of Contents

• Overview
• When to Use
• Quick Start
• Basic Hub Pattern
• Progressive Loading
• Context-Based Selection
• Hub-and-Spoke Architecture
• Hub Responsibilities
• Spoke Characteristics
• Selection Strategies
• Loading Patterns
• Common Use Cases
• Best Practices
• Module References
• Integration with Other Skills
• Exit Criteria

Progressive Loading Patterns

Overview

When To Use

• Cover multiple distinct workflows or domains
• Need to manage context window efficiently
• Have modules that are mutually exclusive based on context
• Require MECW compliance for long-running sessions
• Want to optimize for common paths while supporting edge cases

When NOT To Use

• Project doesn't use the leyline infrastructure patterns
• Simple scripts without service architecture needs

Quick Start

Basic Hub Pattern

## Progressive Loading

**Context A**: Load `modules/loading-patterns.md` for scenario A
**Context B**: Load `modules/selection-strategies.md` for scenario B

**Always Available**: Core utilities, exit criteria, integration points

--help

Context-Based Selection

from leyline import ModuleSelector, MECWMonitor

selector = ModuleSelector(skill_path="my-skill/")
modules = selector.select_modules(
    context={"intent": "git-catchup", "artifacts": ["git", "python"]},
    max_tokens=MECWMonitor().get_safe_budget()
)

--help

Hub-and-Spoke Architecture

Hub Responsibilities

1. Context Detection: Identify user intent, artifacts, workflow type
2. Module Selection: Choose which modules to load based on context
3. Budget Management: Verify MECW compliance before loading
4. Integration Coordination: Provide integration points with other skills
5. Exit Criteria: Define completion criteria across all paths

Spoke Characteristics

1. Single Responsibility: Each module serves one workflow or domain
2. Self-Contained: Modules don't depend on other modules
3. Context-Tagged: Clear indicators of when module applies
4. Token-Budgeted: Known token cost for selection decisions
5. Independently Testable: Can be evaluated in isolation

Selection Strategies

modules/selection-strategies.md

• Intent-based: Load based on detected user goals
• Artifact-based: Load based on detected files/systems
• Budget-aware: Load within available token budget
• Progressive: Load core first, expand as needed
• Mutually-exclusive: Load one path from multiple options

Loading Patterns

modules/loading-patterns.md

• Conditional includes: Dynamic module references
• Lazy loading: Load on first use
• Tiered disclosure: Core → common → edge cases
• Context switching: Change loaded modules mid-session
• Preemptive unloading: Remove unused modules under pressure

Common Use Cases

• Multi-Domain Skills:

  imbue:catchup

  loads git/docs/logs modules by context
• Context-Heavy Analysis: Load relevant modules only, defer deep-dives, unload completed
• Plugin Infrastructure: Mix-and-match infrastructure modules with version checks

Best Practices

1. Design Hub First: Define all possible contexts and module boundaries
2. Tag Modules Clearly: Use YAML frontmatter to indicate context triggers
3. Measure Token Cost: Know the cost of each module for selection
4. Monitor Loading: Track which modules are actually used
5. Validate Paths: Verify all context paths have required modules
6. Document Triggers: Make context detection logic transparent

Module References

• Selection Strategies: See

  modules/selection-strategies.md

  for choosing modules
• Loading Patterns: See

  modules/loading-patterns.md

  for implementation techniques
• Performance Budgeting: See

  modules/performance-budgeting.md

  for token budget model and optimization workflow

Integration with Other Skills

• abstract:modular-skills

  - Uses progressive loading for skill design

• conserve:context-optimization

  - Uses for MECW-compliant loading

• imbue:catchup

  - Uses for context-based module selection
• Plugin authors building multi-workflow skills

dependencies: [leyline:progressive-loading, leyline:mecw-patterns]
progressive_loading: true

--help

Exit Criteria

• Hub clearly defines all module loading contexts
• Each module is tagged with activation context
• Module selection respects MECW constraints
• Token costs measured for all modules
• Context detection logic documented
• Loading paths validated for completeness

Troubleshooting

Common Issues

--verbose