Architecture Overview
Claude Commands Library is built on a modular, extensible architecture that combines several intelligent systems.
Core Components
┌─────────────────────────────────────────────────────────────────┐
│ Claude Commands Library │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Commands │ │ Library │ │ Config │ │
│ │ /prompt │ │ Core + Adapt│ │ JSON files │ │
│ │ /prompt-* │ │ │ │ │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │
│ └────────────┬────┴─────────────────┘ │
│ ▼ │
│ ┌────────────────────────────────────────────────────┐ │
│ │ Phase 0: Prompt Perfection │ │
│ │ Detection → Check → Clarify → Structure → Approve │ │
│ └────────────────────────┬───────────────────────────┘ │
│ │ │
│ ┌─────────────────┼─────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌─────────────┐ ┌──────────────┐ ┌─────────────┐ │
│ │ Hybrid │ │ Predictive │ │ Multi- │ │
│ │Intelligence │ │ Intelligence │ │ Agent │ │
│ │ (agents) │ │ (Phase 0.15)│ │ Research │ │
│ └─────────────┘ └──────────────┘ └─────────────┘ │
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ Caching │ │ Learning │ │ Memory │ │
│ │ Agent results│ │ Patterns │ │ Sessions │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘Directory Structure
.claude/
├── commands/ # Slash command definitions
│ ├── prompt.md
│ ├── prompt-hybrid.md
│ ├── prompt-technical.md
│ ├── prompt-research.md
│ └── ...
│
├── library/ # Reusable components
│ ├── prompt-perfection-core.md # Phase 0 canonical
│ ├── adapters/ # Domain extensions
│ │ ├── technical-adapter.md
│ │ ├── article-adapter.md
│ │ └── hybrid-adapter.md
│ └── intelligence/ # AI systems
│ ├── predictive-intelligence-core.md
│ ├── relationship-mapper.md
│ └── warning-system.md
│
├── config/ # Configuration files
│ ├── complexity-rules.json
│ ├── agent-templates.json
│ ├── cache-config.json
│ ├── learning-config.json
│ └── ai-fluency.json # NEW v4.1
│
├── memory/ # Persistent data
│ ├── project-profile.md # Structured fact store (v4.2)
│ ├── sessions.md
│ ├── prompt-patterns.md
│ └── observations.md
│
├── rules/ # Path-specific rules
│ ├── technical-patterns.md
│ └── command-conventions.md
│
└── cache/ # Cached results
└── agent-results/Key Concepts
1. AI Fluency Framework (NEW v4.1)
Aligned with Anthropic's 4Ds model for effective human-AI collaboration:
- Delegation: Explicit human vs AI task distribution
- Description: 9 criteria (Product, Process, Performance)
- Discernment: Evaluation hints for AI outputs
- Diligence: Track AI content requiring verification
2. Phase 0: The Foundation
Every command starts with Phase 0 - the prompt perfection process. This ensures clarity before execution.
3. Library System
Commands don't duplicate logic. They reference a shared library:
- Core: Universal Phase 0 implementation
- Adapters: Domain-specific extensions
- Intelligence: AI enhancement systems
4. Hybrid Intelligence
Automatic complexity detection determines when to use agents:
- Simple tasks: Fast inline validation
- Complex tasks: Spawn specialized agents
- Research tasks: Multi-agent orchestration
Understand Hybrid Intelligence →
5. Predictive Intelligence
Phase 0.15 provides proactive guidance:
- Journey stage detection
- Domain risk analysis
- Pattern recognition
- Proactive warnings
Discover Predictive Intelligence →
6. Multi-Agent Research
Deep analysis using 2-5 specialized agents:
- Parallel exploration
- Iterative refinement
- Gap-driven research
Learn about Multi-Agent Research →
Data Flow
User Input: "/prompt-technical Add authentication"
│
▼
┌─────────────────────────────────────────┐
│ Command: prompt-technical │
│ │
│ Import: library/prompt-perfection-core │
│ Adapt: library/adapters/technical │
│ Config: config/complexity-rules.json │
└──────────────────┬──────────────────────┘
▼
┌─────────────────────────────────────────┐
│ Phase 0: Prompt Perfection │
│ │
│ 1. Detect language, type, intent │
│ 2. Recall facts from project profile │
│ 3. Check completeness (6 criteria) │
│ 4. Ask only unknown information │
│ 5. Structure perfected prompt │
│ 6. Wait for approval │
└──────────────────┬──────────────────────┘
▼
┌─────────────────────────────────────────┐
│ Complexity-Based Routing │
│ │
│ Score 0-4: → Manual scan │
│ Score 5-9: → Ask user about agent │
│ Score 10+: → Spawn Explore Agent │
│ Score 15+: → Multi-agent verification │
└──────────────────┬──────────────────────┘
▼
┌─────────────────────────────────────────┐
│ Agent Exploration (if needed) │
│ │
│ - Scan project structure │
│ - Detect patterns and conventions │
│ - Find related implementations │
│ - Cache results for 24 hours │
└──────────────────┬──────────────────────┘
▼
┌─────────────────────────────────────────┐
│ Implementation Analysis │
│ │
│ - 2-3 implementation options │
│ - Pros/cons comparison │
│ - Best practices checklist │
│ - Code scaffolding │
└──────────────────┬──────────────────────┘
▼
┌─────────────────────────────────────────┐
│ Learning System Update │
│ │
│ - Record transformation │
│ - Track user modifications │
│ - Update pattern database │
└─────────────────────────────────────────┘Configuration System
All behavior is configuration-driven:
| File | Purpose |
|---|---|
complexity-rules.json | Triggers and thresholds |
agent-templates.json | Agent prompts |
cache-config.json | Caching settings |
learning-config.json | Pattern tracking |
predictive-intelligence.json | Proactive guidance |
ai-fluency.json | 4Ds framework settings (NEW v4.1) |
Next Steps
Dive deeper into specific systems: