frankgpt/v6

Frank v6 - Modular AI Assistant Framework

Version: 6.0
Architecture: Skills-Centric Modular System
Philosophy: Pick up and go - zero environment coupling, maximum portability

---

🚀 Quick Start

Option 1: Core Only (Universal Assistant)

Load just the core for a friendly, mentoring assistant with universal capabilities:

Load: v6/Frank.core.agent.md

You get:

• Upbeat, friendly, mentoring personality
• 7 universal personas (Project Manager, Information Architect, Technical Writer, QA Analyst, Editor, Communications Lead, Business Analyst)
• 8 base commands: /quickstart, /create, /review, /refactor, /document, /communicate, /consult, /help

Option 2: Core + Skills (With Reasoning Techniques)

Add advanced reasoning techniques for complex problem-solving:

Load: 
- v6/Frank.core.agent.md
- v6/skills/style.cot.instructions.md (Chain-of-Thought)
- v6/skills/style.tot.instructions.md (Tree-of-Thought)
- v6/skills/style.craft.instructions.md (C.R.A.F.T. framework)

You get: Core + step-by-step reasoning, multi-path exploration, structured prompt creation

Option 3: Core + Specialty (Domain Expert)

Load a specialty module for domain-specific expertise:

Frank for DevOps:

Load:
- v6/Frank.core.agent.md
- v6/specialties/specialty.devops.instructions.md
Commands: /docker, /ansible, /compose, /traefik

Frank for Data Analysis:

Load:
- v6/Frank.core.agent.md
- v6/specialties/specialty.data-analysis.instructions.md
Commands: /analyze, /query, /visualize, /model, /clean

Frank for IT Service Management:

Load:
- v6/Frank.core.agent.md
- v6/specialties/specialty.itil.instructions.md
Commands: /ticket, /rca, /sop, /itil

See: All Available Specialties

Option 4: Multi-Specialty Composition

Combine multiple specialties for cross-domain expertise:

Load:
- v6/Frank.core.agent.md
- v6/specialties/specialty.devops.instructions.md
- v6/specialties/specialty.data-analysis.instructions.md
- v6/skills/style.advanced-reasoning.instructions.md

You get: DevOps + Data Science hybrid with advanced reasoning

---

📁 Architecture Overview

Frank v6 uses a 3-layer modular architecture:

Layer 1: CORE (required)
└── Frank.core.agent.md - Universal personality and base capabilities

Layer 2: SKILLS (optional, technique-focused)
├── style.craft.instructions.md - C.R.A.F.T. framework for prompts
├── style.cot.instructions.md - Chain-of-Thought reasoning
├── style.tot.instructions.md - Tree-of-Thought reasoning
├── style.rag.instructions.md - Retrieval-Augmented Generation
├── style.advanced-reasoning.instructions.md - Overview of all techniques
├── style.markdown.instructions.md - Markdown formatting standards
└── style.mermaid.instructions.md - Diagram creation

Layer 3: SPECIALTIES (optional, domain-focused)
├── specialty.devops.instructions.md - Docker, Ansible, IaC automation
├── specialty.prompt-engineering.instructions.md - LLM optimization
├── specialty.data-analysis.instructions.md - SQL, Python, statistics
├── specialty.sccm.instructions.md - Endpoint management (SCCM/Intune)
├── specialty.itil.instructions.md - IT service management
└── specialty.TEMPLATE.instructions.md - Create your own specialty

Layer 4: KNOWLEDGE (reference materials)
├── example.CoT-Prompting.md - Chain-of-Thought examples
├── example.ToT-Prompting.md - Tree-of-Thought examples
├── example.RAG-Token.md - RAG examples
├── example.ReAct.md - ReAct protocol examples
├── example.ITILv4.instructions.md - ITIL framework reference
└── example.Meta-Prompting.md - Meta-prompting examples

Key Principle: Load only what you need. Core works alone, skills enhance reasoning, specialties add domain expertise.

---

🎯 Available Specialties

DevOps & Site Reliability Engineering

File: specialty.devops.instructions.md
Commands: /docker, /ansible, /compose, /traefik
Expertise: Container orchestration, infrastructure automation, Traefik routing, safe deployment strategies
Use When: Troubleshooting Docker/Compose, writing Ansible playbooks, designing IaC solutions

Prompt Engineering & LLM Optimization

File: specialty.prompt-engineering.instructions.md
Commands: /optimize, /craft, /reason, /evaluate, /patterns
Expertise: LLM optimization, C.R.A.F.T. framework mastery, reasoning technique integration
Use When: Creating production prompts, optimizing existing prompts, integrating CoT/ToT/RAG

Data Analysis & Visualization

File: specialty.data-analysis.instructions.md
Commands: /analyze, /query, /visualize, /model, /clean
Expertise: SQL, Python (Pandas, Matplotlib, Seaborn), statistical modeling, SCoT methodology
Use When: Analyzing datasets, writing queries, creating visualizations, statistical analysis

Modern Endpoint Management

File: specialty.sccm.instructions.md
Commands: /sccm, /intune, /comanage, /package, /troubleshoot
Expertise: SCCM/Intune, Co-management, compliance policies, Win32 app packaging
Use When: Managing endpoints, deploying apps, configuring compliance, migrating to Intune

IT Service Management (ITIL v4)

File: specialty.itil.instructions.md
Commands: /ticket, /rca, /sop, /itil
Expertise: Incident Management, Problem Management, Knowledge Management, ITIL v4 framework
Use When: Resolving incidents, conducting RCAs, creating IT documentation, applying ITIL principles

---

🛠️ VS Code Integration

Method 1: Workspace Instructions (Recommended)

1. Open VS Code Settings (Ctrl+,)
2. Search for "GitHub Copilot Chat: Instructions File"
3. Set to: ${workspaceFolder}/v6/copilot-instructions.md
4. Reload VS Code

The copilot-instructions.md file pre-configures common loading patterns.

Method 2: Manual Loading

In any Copilot Chat, use #file to reference:

@workspace Load #file:v6/Frank.core.agent.md and #file:v6/specialties/specialty.devops.instructions.md

Now help me troubleshoot this Docker Compose issue...

Method 3: Direct File Reference

Copy the content you need directly into your chat context, or use VS Code's "Add to Chat" feature on the files.

See: copilot-instructions.md for pre-configured patterns

---

💡 Usage Examples

Example 1: Creating a Technical Document

User: "I need to create API documentation for our REST service"

Frank (Core): "I'll guide you through creating comprehensive API documentation.
Let me use the Technical Writer persona and Documentation workflow..."

[Walks through structure, audience, content gathering, drafting]

Example 2: DevOps Troubleshooting

User: "My Docker Compose stack won't start, getting network errors"

Frank (Core + DevOps): "I'll help diagnose this. Triggering DevOps SRE persona.
Let me gather diagnostics..."

[Requests specific outputs, analyzes logs, proposes minimal fix with verification steps]

Example 3: Data Analysis with Reasoning

User: "Analyze Q1 sales data and identify trends"

Frank (Core + Data Analysis + CoT): "I'll analyze this using Structured Chain-of-Thought.

## 1. Clarify & Define
Your objective: Identify sales trends in Q1 data
Key sources: sales table, customers table
Success criteria: Actionable insights with visualizations

## 2. Repository Check
[Reviews existing scripts]

## 3. Plan & Methodology
[Outlines analytical steps]
..."

Example 4: Root Cause Analysis with ITIL

User: "Email server has been slow all week, need to find root cause"

Frank (Core + ITIL): "I'll conduct a root cause analysis using ITIL Problem Management.
Triggering Problem Manager persona with Tree-of-Thought analysis..."

[Gathers timeline, generates hypotheses, evaluates evidence, documents RCA]

Example 5: Multi-Specialty Composition

Load: Core + DevOps + Data Analysis

User: "Help me analyze Docker container metrics and visualize resource usage"

Frank: "This combines my DevOps and Data Analysis expertise.
I'll use Docker diagnostic commands to gather metrics, then Python/Pandas for analysis..."

[Bridges both domains seamlessly]

---

🎨 Creating Custom Specialties

Want to add your own domain expertise? Use the template:

1. Copy the template:

   cp v6/specialties/specialty.TEMPLATE.instructions.md v6/specialties/specialty.legal.instructions.md
   

2. Customize sections:

   • Replace placeholder text with your domain
   • Define 2-5 expert personas
   • Create 3-7 slash commands
   • Document 2-5 key workflows
   • Reference relevant skills

3. Test integration:

   Load: v6/Frank.core.agent.md + v6/specialties/specialty.legal.instructions.md
   

4. Share (optional): Your custom specialty can be shared with others - just distribute the file!

See: specialty.TEMPLATE.instructions.md for detailed guidance

---

📚 Documentation

• ARCHITECTURE.md: Comprehensive architecture guide (500+ lines)

  • Design principles
  • File organization
  • Loading patterns
  • Multi-specialty composition
  • Migration from v4/v5
  • Troubleshooting
  • Version history

• copilot-instructions.md: VS Code integration guide

  • Pre-configured loading patterns
  • Quick start templates
  • Multi-specialty examples

• Individual files: Each skill and specialty has inline documentation

---

🔄 Migration from Earlier Versions

From v5 (FrankGPT.consolidated-instructions.md)

v5 approach: Single monolithic file with all capabilities
v6 approach: Modular - load only what you need

Migration path:

1. Core functionality: Use Frank.core.agent.md (replaces universal personas)
2. IT operations: Use specialty.itil.instructions.md (replaces ITIL/incident workflows)
3. DevOps: Use specialty.devops.instructions.md (replaces Docker/Ansible sections)
4. Prompting: Use specialty.prompt-engineering.instructions.md (replaces prompt optimization)

Benefit: Smaller context window, faster loading, compose only what you need

From v4 (Multiple agents/ files)

v4 approach: Separate agent files (Data Analyst, SCCM Tutor, etc.)
v6 approach: Specialties that compose with shared core

Migration path:

• agents/Data Analyst.agent.md → specialty.data-analysis.instructions.md
• agents/SCCM Tutor.agent.md → specialty.sccm.instructions.md
• Custom agents → Create using specialty.TEMPLATE.instructions.md

Benefit: Shared core personality, multi-specialty composition, portable structure

---

🏗️ Design Principles

1. Portability First

• Zero environment coupling: No hardcoded paths, no system-specific references
• Relative paths only: All cross-references use ../skills/, ../knowledge/ patterns
• "Pick up and go": Copy the v6/ folder to any system and it works

2. Modularity

• Core is self-sufficient: Works alone without dependencies
• Skills enhance: Add reasoning techniques as needed
• Specialties compose: Load multiple domains without conflicts
• Knowledge is reference: Shared examples available to all layers

3. Versioning

• All files tagged: version: 6.0 in frontmatter
• Compatibility tracked: compatibleWith: Frank.core v6+
• Forward compatible: v6+ notation allows future evolution

4. Multi-Specialty Support

• No command conflicts: Each specialty uses domain-specific commands
• Shared skills: Multiple specialties can reference same CoT/ToT/RAG modules
• Conflict resolution: When overlaps exist, documentation explains disambiguation

---

📊 Project Structure

v6/
├── README.md                          ← You are here
├── ARCHITECTURE.md                    ← Detailed architecture guide
├── copilot-instructions.md            ← VS Code integration
├── Frank.core.agent.md                ← Core personality (REQUIRED)
├── skills/                            ← Reasoning techniques (OPTIONAL)
│   ├── style.advanced-reasoning.instructions.md
│   ├── style.cot.instructions.md
│   ├── style.craft.instructions.md
│   ├── style.markdown.instructions.md
│   ├── style.mermaid.instructions.md
│   ├── style.rag.instructions.md
│   └── style.tot.instructions.md
├── specialties/                       ← Domain expertise (OPTIONAL)
│   ├── specialty.data-analysis.instructions.md
│   ├── specialty.devops.instructions.md
│   ├── specialty.itil.instructions.md
│   ├── specialty.prompt-engineering.instructions.md
│   ├── specialty.sccm.instructions.md
│   └── specialty.TEMPLATE.instructions.md
└── knowledge/                         ← Reference examples
    ├── example.CoT-Prompting.md
    ├── example.ITILv4.instructions.md
    ├── example.Meta-Prompting.md
    ├── example.RAG-Token.md
    ├── example.ReAct.md
    └── example.ToT-Prompting.md

Total: 23 files, ~5,600 lines, fully modular

---

🔧 Troubleshooting

Frank isn't responding to specialty commands

Check: Are you loading both Frank.core AND the specialty?

# Correct:
Load: Frank.core.agent.md + specialty.devops.instructions.md

# Incorrect (core alone doesn't have /docker):
Load: Frank.core.agent.md

Commands from multiple specialties conflict

Check: Do the specialties actually conflict, or are they complementary?

• /docker (DevOps) and /analyze (Data Analysis) don't conflict
• If true conflict exists, specify domain: "Use DevOps /troubleshoot" vs "Use Data Analysis workflow"

Skills aren't being applied

Check: Skills are passive references - specialties or core must explicitly invoke them

• Frank.core references C.R.A.F.T. framework for prompt evaluation
• specialty.prompt-engineering deeply integrates all skills
• Loading skills alone without core/specialty won't trigger behaviors

Cross-references not working

Check: All paths are relative from v6/ root

• Correct: ../skills/style.cot.instructions.md
• Incorrect: /skills/style.cot.instructions.md or absolute paths

---

🚀 Roadmap

v6.1 (Future)

• Additional specialties: Security, Cloud Architecture, Database Design
• Enhanced multi-specialty conflict resolution
• Knowledge base expansion with more examples

v7.0 (Future)

• Dynamic specialty loading based on conversation context
• Auto-detection of required skills
• Specialty versioning and compatibility matrix

---

🤝 Contributing

Want to contribute a specialty or improve existing modules?

1. For new specialties: Use specialty.TEMPLATE.instructions.md as your starting point
2. For improvements: Ensure changes maintain v6 compatibility
3. For bug fixes: Update version metadata if behavior changes
4. Share: Custom specialties can be shared as standalone files

Principles:

• Maintain portability (no environment coupling)
• Use relative paths
• Document in frontmatter
• Include examples in workflows
• Test with Frank.core independently

---

📜 Version History

v6.0 (April 2026)

Major refactor: Monolithic → Modular architecture

Changes:

• ✅ Created 3-layer system (Core → Skills → Specialties)
• ✅ Created 6 specialties (itil, devops, prompt-engineering, data-analysis, sccm, TEMPLATE)
• ✅ Zero environment coupling achieved
• ✅ Multi-specialty composition support
• ✅ Full documentation (ARCHITECTURE.md, README.md, LEGACY.md)

Migration: v4/v5 → v6 (see Migration section above)

v5.0 (2024-2025)

• Single consolidated file: FrankGPT.consolidated-instructions.md
• Monolithic approach with all capabilities included
• IT operations focus with ITIL integration

v4.0 (2023-2024)

• Multiple agent files in agents/ folder
• Separate: Data Analyst, SCCM Tutor, custom agents
• Core instructions in instructions/ folder

---

📞 Support

Documentation:

• Quick start: This file (README.md)
• Architecture deep-dive: ARCHITECTURE.md
• VS Code setup: copilot-instructions.md
• Template guide: specialty.TEMPLATE.instructions.md

Need help?

• Review ARCHITECTURE.md for detailed patterns
• Check individual specialty files for domain-specific guidance
• Load specialty.prompt-engineering.instructions.md to optimize your own prompts

---

📄 License

This is a personal AI assistant framework. Use, modify, and extend as needed for your projects.

---

Frank v6: Modular. Portable. Composable. Pick up and go. 🚀