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SuperClaude Architecture

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SuperClaude Architecture

Last Updated: 2025-10-14 Version: 4.1.5

๐Ÿ“‹ Table of Contents

  1. System Overview
  2. Core Architecture
  3. PM Agent Mode: The Meta-Layer
  4. Component Relationships
  5. Serena MCP Integration
  6. PDCA Engine
  7. Data Flow
  8. Extension Points

System Overview

What is SuperClaude?

SuperClaude is a Context-Oriented Configuration Framework that transforms Claude Code into a structured development platform. It is NOT standalone software with running processes - it is a collection of .md instruction files that Claude Code reads to adopt specialized behaviors.

Key Components

SuperClaude Framework
โ”œโ”€โ”€ Commands (26)      โ†’ Workflow patterns
โ”œโ”€โ”€ Agents (16)        โ†’ Domain expertise
โ”œโ”€โ”€ Modes (7)          โ†’ Behavioral modifiers
โ”œโ”€โ”€ MCP Servers (8)    โ†’ External tool integrations
โ””โ”€โ”€ PM Agent Mode      โ†’ Meta-layer orchestration (Always-Active)

Version Information

  • Current Version: 4.1.5
  • Commands: 26 slash commands (/sc:*)
  • Agents: 16 specialized domain experts
  • Modes: 7 behavioral modes
  • MCP Servers: 8 integrations (Context7, Sequential, Magic, Playwright, Morphllm, Serena, Tavily, Chrome DevTools)

Core Architecture

Context-Oriented Configuration

SuperClaude's architecture is built on a simple principle: behavioral modification through structured context files.

User Input
    โ†“
Context Loading (CLAUDE.md imports)
    โ†“
Command Detection (/sc:* pattern)
    โ†“
Agent Activation (manual or auto)
    โ†“
Mode Application (flags or triggers)
    โ†“
MCP Tool Coordination
    โ†“
Output Generation

Directory Structure

~/.claude/
โ”œโ”€โ”€ CLAUDE.md                   # Main context with @imports
โ”œโ”€โ”€ FLAGS.md                    # Flag definitions
โ”œโ”€โ”€ RULES.md                    # Core behavioral rules
โ”œโ”€โ”€ PRINCIPLES.md               # Guiding principles
โ”œโ”€โ”€ MODE_*.md                   # 7 behavioral modes
โ”œโ”€โ”€ MCP_*.md                    # 8 MCP server integrations
โ”œโ”€โ”€ agents/                     # 16 specialized agents
โ”‚   โ”œโ”€โ”€ pm-agent.md            # ๐Ÿ†• Meta-layer orchestrator
โ”‚   โ”œโ”€โ”€ backend-architect.md
โ”‚   โ”œโ”€โ”€ frontend-architect.md
โ”‚   โ”œโ”€โ”€ security-engineer.md
โ”‚   โ””โ”€โ”€ ... (13 more)
โ””โ”€โ”€ commands/sc/               # 26 workflow commands
    โ”œโ”€โ”€ pm.md                  # ๐Ÿ†• PM Agent command
    โ”œโ”€โ”€ implement.md
    โ”œโ”€โ”€ analyze.md
    โ””โ”€โ”€ ... (23 more)

PM Agent Mode: The Meta-Layer

Position in Architecture

PM Agent operates as a meta-layer above all other components:

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚         PM Agent Mode (Meta-Layer)          โ”‚
โ”‚   โ€ข Always Active (Session Start)           โ”‚
โ”‚   โ€ข Context Preservation                     โ”‚
โ”‚   โ€ข PDCA Self-Evaluation                     โ”‚
โ”‚   โ€ข Knowledge Management                     โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                    โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚          Specialist Agents (16)              โ”‚
โ”‚   backend-architect, security-engineer, etc. โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                    โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚           Commands & Modes                   โ”‚
โ”‚   /sc:implement, /sc:analyze, etc.          โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                    โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚            MCP Tool Layer                    โ”‚
โ”‚   Context7, Sequential, Magic, etc.         โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

PM Agent Responsibilities

  1. Session Lifecycle Management

    • Auto-activation at session start
    • Context restoration from Serena MCP memory
    • User report generation (ๅ‰ๅ›ž/้€ฒๆ—/ไปŠๅ›ž/่ชฒ้กŒ)
  2. PDCA Cycle Execution

    • Plan: Hypothesis generation
    • Do: Experimentation with checkpoints
    • Check: Self-evaluation
    • Act: Knowledge extraction
  3. Documentation Strategy

    • Temporary documentation (docs/temp/)
    • Formal patterns (docs/patterns/)
    • Mistake records (docs/mistakes/)
    • Knowledge evolution to CLAUDE.md
  4. Sub-Agent Orchestration

    • Auto-delegation to specialists
    • Context coordination
    • Quality gate validation
    • Progress monitoring

Component Relationships

Commands โ†’ Agents โ†’ Modes โ†’ MCP

User: "/sc:implement authentication" --security
         โ†“
    [Command Layer]
    commands/sc/implement.md
         โ†“
    [Agent Auto-Activation]
    agents/security-engineer.md
    agents/backend-architect.md
         โ†“
    [Mode Application]
    MODE_Task_Management.md (TodoWrite)
         โ†“
    [MCP Tool Coordination]
    Context7 (auth patterns)
    Sequential (complex analysis)
         โ†“
    [PM Agent Meta-Layer]
    Document learnings โ†’ docs/patterns/

Activation Flow

  1. Explicit Command: User types /sc:implement

    • Loads commands/sc/implement.md
    • Activates related agents (backend-architect, etc.)
  2. Agent Activation: @agent-security or auto-detected

    • Loads agent expertise context
    • May activate related MCP servers
  3. Mode Application: --brainstorm flag or keywords

    • Modifies interaction style
    • Enables specific behaviors
  4. PM Agent Meta-Layer: Always active

    • Monitors all interactions
    • Documents learnings
    • Preserves context across sessions

Serena MCP Integration

Memory Operations

Serena MCP provides semantic code analysis and session persistence through memory operations:

Session Start:
  PM Agent โ†’ list_memories()
  PM Agent โ†’ read_memory("pm_context")
  PM Agent โ†’ read_memory("last_session")
  PM Agent โ†’ read_memory("next_actions")
  PM Agent โ†’ Report to User

During Work (every 30min):
  PM Agent โ†’ write_memory("checkpoint", progress)
  PM Agent โ†’ write_memory("decision", rationale)

Session End:
  PM Agent โ†’ write_memory("last_session", summary)
  PM Agent โ†’ write_memory("next_actions", todos)
  PM Agent โ†’ write_memory("pm_context", complete_state)

Memory Structure

json
{
  "pm_context": {
    "project": "SuperClaude_Framework",
    "current_phase": "Phase 1: Documentation",
    "active_tasks": ["ARCHITECTURE.md", "ROADMAP.md"],
    "architecture": "Context-Oriented Configuration",
    "patterns": ["PDCA Cycle", "Session Lifecycle"]
  },
  "last_session": {
    "date": "2025-10-14",
    "accomplished": ["PM Agent mode design", "Salvaged implementations"],
    "issues": ["Serena MCP not configured"],
    "learned": ["Session Lifecycle pattern", "PDCA automation"]
  },
  "next_actions": [
    "Create docs/Development/ structure",
    "Write ARCHITECTURE.md",
    "Configure Serena MCP server"
  ]
}

PDCA Engine

Continuous Improvement Cycle

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚    Plan     โ”‚ โ†’ write_memory("plan", goal)
โ”‚   (ไปฎ่ชฌ)    โ”‚ โ†’ docs/temp/hypothesis-YYYY-MM-DD.md
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”˜
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚     Do      โ”‚ โ†’ TodoWrite tracking
โ”‚   (ๅฎŸ้จ“)    โ”‚ โ†’ write_memory("checkpoint", progress)
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ†’ docs/temp/experiment-YYYY-MM-DD.md
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚   Check     โ”‚ โ†’ think_about_task_adherence()
โ”‚   (่ฉ•ไพก)    โ”‚ โ†’ think_about_whether_you_are_done()
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ†’ docs/temp/lessons-YYYY-MM-DD.md
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚    Act      โ”‚ โ†’ Success: docs/patterns/[name].md
โ”‚   (ๆ”นๅ–„)    โ”‚ โ†’ Failure: docs/mistakes/mistake-*.md
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ†’ Update CLAUDE.md
       โ†“
   [Repeat]

Documentation Evolution

Trial-and-Error (docs/temp/)
    โ†“
Success โ†’ Formal Pattern (docs/patterns/)
    โ†“
Accumulate Knowledge
    โ†“
Extract Best Practices โ†’ CLAUDE.md (Global Rules)
Mistake Detection (docs/temp/)
    โ†“
Root Cause Analysis โ†’ docs/mistakes/
    โ†“
Prevention Checklist
    โ†“
Update Anti-Patterns โ†’ CLAUDE.md

Data Flow

Session Lifecycle Data Flow

Session Start:
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚ Claude Code  โ”‚
โ”‚   Startup    โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚  PM Agent    โ”‚ list_memories()
โ”‚  Activation  โ”‚ read_memory("pm_context")
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚   Serena     โ”‚ Return: pm_context,
โ”‚     MCP      โ”‚          last_session,
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜          next_actions
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚  Context     โ”‚ Restore project state
โ”‚ Restoration  โ”‚ Generate user report
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
       โ†“
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚    User      โ”‚ ๅ‰ๅ›ž: [summary]
โ”‚   Report     โ”‚ ้€ฒๆ—: [status]
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ ไปŠๅ›ž: [actions]
                 ่ชฒ้กŒ: [blockers]

Implementation Data Flow

User Request โ†’ PM Agent Analyzes
    โ†“
PM Agent โ†’ Delegate to Specialist Agents
    โ†“
Specialist Agents โ†’ Execute Implementation
    โ†“
Implementation Complete โ†’ PM Agent Documents
    โ†“
PM Agent โ†’ write_memory("checkpoint", progress)
PM Agent โ†’ docs/temp/experiment-*.md
    โ†“
Success โ†’ docs/patterns/ | Failure โ†’ docs/mistakes/
    โ†“
Update CLAUDE.md (if global pattern)

Extension Points

Adding New Components

1. New Command

markdown
File: ~/.claude/commands/sc/new-command.md
Structure:
  - Metadata (name, category, complexity)
  - Triggers (when to use)
  - Workflow Pattern (step-by-step)
  - Examples

Integration:
  - Auto-loads when user types /sc:new-command
  - Can activate related agents
  - PM Agent automatically documents usage patterns

2. New Agent

markdown
File: ~/.claude/agents/new-specialist.md
Structure:
  - Metadata (name, category)
  - Triggers (keywords, file types)
  - Behavioral Mindset
  - Focus Areas

Integration:
  - Auto-activates on trigger keywords
  - Manual activation: @agent-new-specialist
  - PM Agent orchestrates with other agents

3. New Mode

markdown
File: ~/.claude/MODE_NewMode.md
Structure:
  - Activation Triggers (flags, keywords)
  - Behavioral Modifications
  - Interaction Patterns

Integration:
  - Flag: --new-mode
  - Auto-activation on complexity threshold
  - Modifies all agent behaviors

4. New MCP Server

json
File: ~/.claude/.claude.json
{
  "mcpServers": {
    "new-server": {
      "command": "npx",
      "args": ["-y", "new-server-mcp@latest"]
    }
  }
}
markdown
File: ~/.claude/MCP_NewServer.md
Structure:
  - Purpose (what this server provides)
  - Triggers (when to use)
  - Integration (how to coordinate with other tools)

PM Agent Integration for Extensions

All new components automatically integrate with PM Agent meta-layer:

  1. Session Lifecycle: New components' usage tracked across sessions
  2. PDCA Cycle: Patterns extracted from new component usage
  3. Documentation: Learnings automatically documented
  4. Orchestration: PM Agent coordinates new components with existing ones

Architecture Principles

1. Simplicity First

  • No executing code, only context files
  • No performance systems, only instructional patterns
  • No detection engines, Claude Code does pattern matching

2. Context-Oriented

  • Behavior modification through structured context
  • Import system for modular context loading
  • Clear trigger patterns for activation

3. Meta-Layer Design

  • PM Agent orchestrates without interfering
  • Specialist agents work transparently
  • Users interact with cohesive system

4. Knowledge Accumulation

  • Every experience generates learnings
  • Mistakes documented with prevention
  • Patterns extracted to reusable knowledge

5. Session Continuity

  • Context preserved across sessions
  • No re-explanation needed
  • Seamless resumption from last checkpoint

Technical Considerations

Performance

  • Framework is pure context (no runtime overhead)
  • Token efficiency through dynamic MCP loading
  • Strategic context caching for related phases

Scalability

  • Unlimited commands/agents/modes through context files
  • Modular architecture supports independent development
  • PM Agent meta-layer handles coordination complexity

Maintainability

  • Clear separation of concerns (Commands/Agents/Modes)
  • Self-documenting through PDCA cycle
  • Living documentation evolves with usage

Extensibility

  • Drop-in new contexts without code changes
  • MCP servers add capabilities externally
  • PM Agent auto-integrates new components

Future Architecture

Planned Enhancements

  1. Auto-Activation System

    • PM Agent activates automatically at session start
    • No manual invocation needed
  2. Enhanced Memory Operations

    • Full Serena MCP integration
    • Cross-project knowledge sharing
    • Pattern recognition across sessions
  3. PDCA Automation

    • Automatic documentation lifecycle
    • AI-driven pattern extraction
    • Self-improving knowledge base
  4. Multi-Project Orchestration

    • PM Agent coordinates across projects
    • Shared learnings and patterns
    • Unified knowledge management

Summary

SuperClaude's architecture is elegantly simple: structured context files that Claude Code reads to adopt sophisticated behaviors. The addition of PM Agent mode as a meta-layer transforms this from a collection of tools into a continuously learning, self-improving development platform.

Key Architectural Innovation: PM Agent meta-layer provides:

  • Always-active foundation layer
  • Context preservation across sessions
  • PDCA self-evaluation and learning
  • Systematic knowledge management
  • Seamless orchestration of specialist agents

This architecture enables SuperClaude to function as a ๆœ€้ซ˜ๅธไปคๅฎ˜ (Supreme Commander) that orchestrates all development activities while continuously learning and improving from every interaction.


Last Verified: 2025-10-14 Next Review: 2025-10-21 (1 week) Version: 4.1.5