gh-francyjglisboa-agent-skill-creator/docs

Documentation Index

Complete documentation for Agent-Skill-Creator v2.1 with AgentDB learning capabilities.

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🚀 Quick Start (New Users)

Start with these in order:

1. USER_BENEFITS_GUIDE.md ⭐ BEST STARTING POINT

   • What AgentDB learning means for you
   • Real examples of progressive improvement
   • Time savings and value you get
   • Zero-effort benefits explained

2. TRY_IT_YOURSELF.md

   • 5-minute hands-on demo
   • Step-by-step verification
   • See learning capabilities in action

3. QUICK_VERIFICATION_GUIDE.md

   • Command reference and cheat sheet
   • How to check learning is working
   • Quick queries and examples

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🔬 Learning & Verification

LEARNING_VERIFICATION_REPORT.md

Comprehensive 15-section verification report proving all learning capabilities work:

• Reflexion Memory verification (episodes)
• Skill Library verification
• Causal Memory verification (cause-effect relationships)
• Mathematical validation proofs
• Complete technical evidence

Use when: You want complete technical proof or deep understanding of how learning works.

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🏗️ Architecture & Design

CLAUDE_SKILLS_ARCHITECTURE.md

Complete guide to Claude Skills architecture:

• Simple Skills vs Complex Skill Suites
• When to use each pattern
• Architecture decision process
• Component organization
• Best practices

Use when: Understanding skill structure or making architectural decisions.

PIPELINE_ARCHITECTURE.md

Detailed pipeline architecture documentation:

• 5-phase creation process
• Data flow and transformations
• Integration points
• Performance optimization

Use when: Understanding the creation pipeline or optimizing performance.

INTERNAL_FLOW_ANALYSIS.md

Internal flow analysis and decision points:

• Phase-by-phase analysis
• Decision logic at each stage
• Error handling and recovery
• Quality assurance

Use when: Debugging issues or understanding internal mechanisms.

DECISION_LOGIC.md

Decision framework for agent creation:

• Template selection logic
• API selection criteria
• Architecture choice reasoning
• Quality metrics

Use when: Understanding how decisions are made or improving decision quality.

NAMING_CONVENTIONS.md

Naming standards and conventions:

• "-cskill" suffix explained
• Naming patterns for skills
• Directory structure conventions
• Best practices

Use when: Creating skills or maintaining consistency.

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📋 Project Information

CHANGELOG.md

Version history and updates:

• Release notes
• Feature additions
• Bug fixes
• Breaking changes

Use when: Checking what's new or tracking changes between versions.

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📚 Documentation Map

By Use Case

I want to understand what learning does for me: → USER_BENEFITS_GUIDE.md

I want to verify learning is working: → TRY_IT_YOURSELF.md → QUICK_VERIFICATION_GUIDE.md

I want technical proof: → LEARNING_VERIFICATION_REPORT.md

I want to understand architecture: → CLAUDE_SKILLS_ARCHITECTURE.md → PIPELINE_ARCHITECTURE.md

I want to understand decisions: → DECISION_LOGIC.md → INTERNAL_FLOW_ANALYSIS.md

I want naming guidelines: → NAMING_CONVENTIONS.md

I want to see what's changed: → CHANGELOG.md

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🎯 Recommended Reading Paths

For End Users

1. USER_BENEFITS_GUIDE.md (understand value)
2. TRY_IT_YOURSELF.md (hands-on demo)
3. QUICK_VERIFICATION_GUIDE.md (reference)

For Developers

1. CLAUDE_SKILLS_ARCHITECTURE.md (architecture)
2. PIPELINE_ARCHITECTURE.md (implementation)
3. LEARNING_VERIFICATION_REPORT.md (technical proof)
4. DECISION_LOGIC.md (decision framework)

For Contributors

1. NAMING_CONVENTIONS.md (standards)
2. INTERNAL_FLOW_ANALYSIS.md (internals)
3. PIPELINE_ARCHITECTURE.md (architecture)
4. CHANGELOG.md (history)

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🔗 Related Files

In root directory:

• SKILL.md - Main skill definition (agent-creator implementation)
• README.md - Project overview and quick start
• test_agentdb_learning.py - Automated learning verification script

In integrations/ directory:

• agentdb_bridge.py - AgentDB integration layer
• agentdb_real_integration.py - Real AgentDB CLI bridge
• learning_feedback.py - Learning feedback system
• validation_system.py - Mathematical validation

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📊 Documentation Statistics

Category	Files	Total Size
User Guides	3	~28 KB
Learning & Verification	1	~15 KB
Architecture & Design	5	~50 KB
Project Information	1	~5 KB
Total	10	~98 KB

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💡 Quick Tips

First time here? Start with USER_BENEFITS_GUIDE.md

Want to verify? Run: python3 ../test_agentdb_learning.py

Need quick reference? Check QUICK_VERIFICATION_GUIDE.md

Technical details? Read LEARNING_VERIFICATION_REPORT.md

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Last Updated: October 23, 2025 Version: 2.1 Status: ✅ All learning capabilities verified and operational