SuperClaude/docs/Reference/advanced-workflows.md
kazuki nakai 050d5ea2ab
refactor: PEP8 compliance - directory rename and code formatting (#425)
* fix(orchestration): add WebFetch auto-trigger for infrastructure configuration

Problem: Infrastructure configuration changes (e.g., Traefik port settings)
were being made based on assumptions without consulting official documentation,
violating the 'Evidence > assumptions' principle in PRINCIPLES.md.

Solution:
- Added Infrastructure Configuration Validation section to MODE_Orchestration.md
- Auto-triggers WebFetch for infrastructure tools (Traefik, nginx, Docker, etc.)
- Enforces MODE_DeepResearch activation for investigation
- BLOCKS assumption-based configuration changes

Testing: Verified WebFetch successfully retrieves Traefik official docs (port 80 default)

This prevents production outages from infrastructure misconfiguration by ensuring
all technical recommendations are backed by official documentation.

* feat: Add PM Agent (Project Manager Agent) for seamless orchestration

Introduces PM Agent as the default orchestration layer that coordinates
all sub-agents and manages workflows automatically.

Key Features:
- Default orchestration: All user interactions handled by PM Agent
- Auto-delegation: Intelligent sub-agent selection based on task analysis
- Docker Gateway integration: Zero-token baseline with dynamic MCP loading
- Self-improvement loop: Automatic documentation of patterns and mistakes
- Optional override: Users can specify sub-agents explicitly if desired

Architecture:
- Agent spec: SuperClaude/Agents/pm-agent.md
- Command: SuperClaude/Commands/pm.md
- Updated docs: README.md (15→16 agents), agents.md (new Orchestration category)

User Experience:
- Default: PM Agent handles everything (seamless, no manual routing)
- Optional: Explicit --agent flag for direct sub-agent access
- Both modes available simultaneously (no user downside)

Implementation Status:
-  Specification complete
-  Documentation complete
-  Prototype implementation needed
-  Docker Gateway integration needed
-  Testing and validation needed

Refs: kazukinakai/docker-mcp-gateway (IRIS MCP Gateway integration)

* feat: Add Agent Orchestration rules for PM Agent default activation

Implements PM Agent as the default orchestration layer in RULES.md.

Key Changes:
- New 'Agent Orchestration' section (CRITICAL priority)
- PM Agent receives ALL user requests by default
- Manual override with @agent-[name] bypasses PM Agent
- Agent Selection Priority clearly defined:
  1. Manual override → Direct routing
  2. Default → PM Agent → Auto-delegation
  3. Delegation based on keywords, file types, complexity, context

User Experience:
- Default: PM Agent handles everything (seamless)
- Override: @agent-[name] for direct specialist access
- Transparent: PM Agent reports delegation decisions

This establishes PM Agent as the orchestration layer while
respecting existing auto-activation patterns and manual overrides.

Next Steps:
- Local testing in agiletec project
- Iteration based on actual behavior
- Documentation updates as needed

* refactor(pm-agent): redesign as self-improvement meta-layer

Problem Resolution:
PM Agent's initial design competed with existing auto-activation for task routing,
creating confusion about orchestration responsibilities and adding unnecessary complexity.

Design Change:
Redefined PM Agent as a meta-layer agent that operates AFTER specialist agents
complete tasks, focusing on:
- Post-implementation documentation and pattern recording
- Immediate mistake analysis with prevention checklists
- Monthly documentation maintenance and noise reduction
- Pattern extraction and knowledge synthesis

Two-Layer Orchestration System:
1. Task Execution Layer: Existing auto-activation handles task routing (unchanged)
2. Self-Improvement Layer: PM Agent meta-layer handles documentation (new)

Files Modified:
- SuperClaude/Agents/pm-agent.md: Complete rewrite with meta-layer design
  - Category: orchestration → meta
  - Triggers: All user interactions → Post-implementation, mistakes, monthly
  - Behavioral Mindset: Continuous learning system
  - Self-Improvement Workflow: BEFORE/DURING/AFTER/MISTAKE RECOVERY/MAINTENANCE

- SuperClaude/Core/RULES.md: Agent Orchestration section updated
  - Split into Task Execution Layer + Self-Improvement Layer
  - Added orchestration flow diagram
  - Clarified PM Agent activates AFTER task completion

- README.md: Updated PM Agent description
  - "orchestrates all interactions" → "ensures continuous learning"

- Docs/User-Guide/agents.md: PM Agent section rewritten
  - Section: Orchestration Agent → Meta-Layer Agent
  - Expertise: Project orchestration → Self-improvement workflow executor
  - Examples: Task coordination → Post-implementation documentation

- PR_DOCUMENTATION.md: Comprehensive PR documentation added
  - Summary, motivation, changes, testing, breaking changes
  - Two-layer orchestration system diagram
  - Verification checklist

Integration Validated:
Tested with agiletec project's self-improvement-workflow.md:
 PM Agent aligns with existing BEFORE/DURING/AFTER/MISTAKE RECOVERY phases
 Complements (not competes with) existing workflow
 agiletec workflow defines WHAT, PM Agent defines WHO executes it

Breaking Changes: None
- Existing auto-activation continues unchanged
- Specialist agents unaffected
- User workflows remain the same
- New capability: Automatic documentation and knowledge maintenance

Value Proposition:
Transforms SuperClaude into a continuously learning system that accumulates
knowledge, prevents recurring mistakes, and maintains fresh documentation
without manual intervention.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add Claude Code conversation history management research

Research covering .jsonl file structure, performance impact, and retention policies.

Content:
- Claude Code .jsonl file format and message types
- Performance issues from GitHub (memory leaks, conversation compaction)
- Retention policies (consumer vs enterprise)
- Rotation recommendations based on actual data
- File history snapshot tracking mechanics

Source: Moved from agiletec project (research applicable to all Claude Code projects)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: add Development documentation structure

Phase 1: Documentation Structure complete

- Add Docs/Development/ directory for development documentation
- Add ARCHITECTURE.md - System architecture with PM Agent meta-layer
- Add ROADMAP.md - 5-phase development plan with checkboxes
- Add TASKS.md - Daily task tracking with progress indicators
- Add PROJECT_STATUS.md - Current status dashboard and metrics
- Add pm-agent-integration.md - Implementation guide for PM Agent mode

This establishes comprehensive documentation foundation for:
- System architecture understanding
- Development planning and tracking
- Implementation guidance
- Progress visibility

Related: #pm-agent-mode #documentation #phase-1

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat: PM Agent session lifecycle and PDCA implementation

Phase 2: PM Agent Mode Integration (Design Phase)

Commands/pm.md updates:
- Add "Always-Active Foundation Layer" concept
- Add Session Lifecycle (Session Start/During Work/Session End)
- Add PDCA Cycle (Plan/Do/Check/Act) automation
- Add Serena MCP Memory Integration (list/read/write_memory)
- Document auto-activation triggers

Agents/pm-agent.md updates:
- Add Session Start Protocol (MANDATORY auto-activation)
- Add During Work PDCA Cycle with example workflows
- Add Session End Protocol with state preservation
- Add PDCA Self-Evaluation Pattern
- Add Documentation Strategy (temp → patterns/mistakes)
- Add Memory Operations Reference

Key Features:
- Session start auto-activation for context restoration
- 30-minute checkpoint saves during work
- Self-evaluation with think_about_* operations
- Systematic documentation lifecycle
- Knowledge evolution to CLAUDE.md

Implementation Status:
-  Design complete (Commands/pm.md, Agents/pm-agent.md)
-  Implementation pending (Core components)
-  Serena MCP integration pending

Salvaged from mistaken development in ~/.claude directory

Related: #pm-agent-mode #session-lifecycle #pdca-cycle #phase-2

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* fix: disable Serena MCP auto-browser launch

Disable web dashboard and GUI log window auto-launch in Serena MCP server
to prevent intrusive browser popups on startup. Users can still manually
access the dashboard at http://localhost:24282/dashboard/ if needed.

Changes:
- Add CLI flags to Serena run command:
  - --enable-web-dashboard false
  - --enable-gui-log-window false
- Ensures Git-tracked configuration (no reliance on ~/.serena/serena_config.yml)
- Aligns with AIRIS MCP Gateway integration approach

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* refactor: rename directories to lowercase for PEP8 compliance

- Rename superclaude/Agents -> superclaude/agents
- Rename superclaude/Commands -> superclaude/commands
- Rename superclaude/Core -> superclaude/core
- Rename superclaude/Examples -> superclaude/examples
- Rename superclaude/MCP -> superclaude/mcp
- Rename superclaude/Modes -> superclaude/modes

This change follows Python PEP8 naming conventions for package directories.

* style: fix PEP8 violations and update package name to lowercase

Changes:
- Format all Python files with black (43 files reformatted)
- Update package name from 'SuperClaude' to 'superclaude' in pyproject.toml
- Fix import statements to use lowercase package name
- Add missing imports (timedelta, __version__)
- Remove old SuperClaude.egg-info directory

PEP8 violations reduced from 2672 to 701 (mostly E501 line length due to black's 88 char vs flake8's 79 char limit).

* docs: add PM Agent development documentation

Add comprehensive PM Agent development documentation:
- PM Agent ideal workflow (7-phase autonomous cycle)
- Project structure understanding (Git vs installed environment)
- Installation flow understanding (CommandsComponent behavior)
- Task management system (current-tasks.md)

Purpose: Eliminate repeated explanations and enable autonomous PDCA cycles

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(pm-agent): add self-correcting execution and warning investigation culture

## Changes

### superclaude/commands/pm.md
- Add "Self-Correcting Execution" section with root cause analysis protocol
- Add "Warning/Error Investigation Culture" section enforcing zero-tolerance for dismissal
- Define error detection protocol: STOP → Investigate → Hypothesis → Different Solution → Execute
- Document anti-patterns (retry without understanding) and correct patterns (research-first)

### docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md
- Add PDCA workflow hypothesis document for PM Agent autonomous enhancement

## Rationale

PM Agent must never retry failed operations without understanding root causes.
All warnings and errors require investigation via context7/WebFetch/documentation
to ensure production-quality code and prevent technical debt accumulation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

* feat(installer): add airis-mcp-gateway MCP server option

## Changes

- Add airis-mcp-gateway to MCP server options in installer
- Configuration: GitHub-based installation via uvx
- Repository: https://github.com/oraios/airis-mcp-gateway
- Purpose: Dynamic MCP Gateway for zero-token baseline and on-demand tool loading

## Implementation

Added to setup/components/mcp.py self.mcp_servers dictionary with:
- install_method: github
- install_command: uvx test installation
- run_command: uvx runtime execution
- required: False (optional server)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

---------

Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local>
Co-authored-by: Claude <noreply@anthropic.com>
2025-10-14 08:47:09 +05:30

7.9 KiB

SuperClaude Advanced Workflows Collection

Status: Status: Current - Complex command sequences and context combinations for sophisticated projects.

Advanced Usage Guide: Patterns for complex projects using multiple commands, agents, and careful context management within Claude Code conversations.

Overview and Usage Guide

Purpose: Advanced SuperClaude patterns for complex, multi-step projects that require careful sequencing of commands and context management.

Important: These are conversation patterns, not executing workflows. All work happens within Claude Code based on context provided.

Key Concepts:

  • Command sequences within a conversation
  • Context layering through multiple agents
  • Progressive refinement approaches
  • Project phase management (manual, not automated)

Multi-Context Project Patterns

Full-Stack Development Sequence

# E-commerce platform using multiple contexts
# Step 1: Architecture context
@agent-system-architect "design e-commerce architecture"

# Step 2: Security requirements
@agent-security "define security requirements for payments"

# Step 3: Backend implementation
/sc:implement "API with authentication and payment processing"
# Claude uses accumulated context from previous steps

# Step 4: Frontend implementation
@agent-frontend-architect "design responsive UI"
/sc:implement "React frontend with TypeScript"

# Step 5: Review
/sc:analyze . --focus quality

# Note: Each step builds context within the conversation
# No actual coordination or parallel execution occurs

Problem-Solving Workflow

# Complex troubleshooting approach
# Step 1: Problem understanding
/sc:troubleshoot "application performance issues"

# Step 2: Expert analysis
@agent-performance-engineer "analyze potential bottlenecks"
@agent-backend-architect "review architecture for issues"

# Step 3: Solution design
/sc:design "performance improvement plan"

# Step 4: Implementation
/sc:implement "performance optimizations"

# Context accumulates but doesn't execute

Complex Project Phases

Project Initialization Pattern

# Starting a new project
# Discovery phase
/sc:brainstorm "project concept"
# Claude explores requirements

# Planning phase
/sc:design "system architecture"
@agent-system-architect "review and refine"

# Documentation
/sc:document --type architecture
/sc:save "project-plan"
# Creates summary for your records (not persistent storage)

Incremental Development Pattern

# Building features incrementally
# Feature 1: Authentication
/sc:implement "user authentication"
/sc:test --focus security
/sc:document --type api

# Feature 2: User Profiles (builds on auth context)
/sc:implement "user profile management"
/sc:test --focus functionality

# Feature 3: Admin Dashboard (uses previous context)
/sc:implement "admin dashboard"
@agent-frontend-architect "ensure consistency"

# Each feature builds on conversation context

Migration Project Pattern

# Legacy system migration
# Phase 1: Analysis
/sc:load legacy-system/
/sc:analyze . --focus architecture --verbose
# Claude builds understanding

# Phase 2: Planning
@agent-system-architect "design migration strategy"
/sc:workflow "create migration plan"

# Phase 3: Implementation
/sc:implement "compatibility layer"
/sc:implement "new system components"

# Phase 4: Validation
/sc:test --focus compatibility
/sc:document --type migration

# Manual phases, not automated workflow

Enterprise-Scale Patterns

Large Codebase Analysis

# Systematic analysis of large projects
# Overview
/sc:analyze . --overview
# Get high-level understanding

# Focused analysis by module
/sc:analyze auth-module/ --focus security
/sc:analyze api-module/ --focus quality
/sc:analyze frontend/ --focus performance

# Synthesis
@agent-system-architect "synthesize findings"
/sc:workflow "improvement recommendations"

# Note: Sequential analysis, not parallel

Multi-Technology Projects

# Projects with diverse tech stacks
# Backend (Python)
@agent-python-expert "implement FastAPI backend"
/sc:implement "Python API with async support"

# Frontend (React)
@agent-frontend-architect "implement React frontend"
/sc:implement "TypeScript React application"

# Mobile (React Native)
/sc:implement "React Native mobile app"

# Infrastructure
@agent-devops-architect "design deployment"
/sc:implement "Docker configuration"

# Each technology addressed sequentially

Quality Assurance Workflows

Comprehensive Review Pattern

# Multi-aspect code review
# Quality review
/sc:analyze . --focus quality
@agent-quality-engineer "identify improvements"

# Security review
/sc:analyze . --focus security
@agent-security "check for vulnerabilities"

# Architecture review
@agent-system-architect "evaluate design"

# Performance review
@agent-performance-engineer "suggest optimizations"

# Consolidated improvements
/sc:improve . --fix

# Sequential reviews, not parallel analysis

Testing Strategy Pattern

# Comprehensive testing approach
# Test planning
/sc:design "testing strategy"

# Unit tests
/sc:test --type unit
# Claude generates unit test code

# Integration tests
/sc:test --type integration
# Claude generates integration test code

# E2E tests
/sc:test --type e2e
# Claude suggests E2E test scenarios

# Documentation
/sc:document --type testing

# Test code generation, not execution

Session Management Patterns

Long Project Sessions

# Managing context in long conversations
# Start with context
/sc:load project/

# Work progressively
/sc:implement "feature A"
/sc:implement "feature B"
# Context accumulates

# Create checkpoint
/sc:save "session-checkpoint"
# Creates summary for your notes

# Continue work
/sc:implement "feature C"

# Final summary
/sc:reflect
# Reviews conversation progress

Context Refresh Pattern

# When conversation gets too long
# Save current state
/sc:save "work-complete"
# Copy output for next conversation

# In new conversation:
/sc:load project/
"Previous work: [paste summary]"
# Manually restore context

# Continue work
/sc:implement "next feature"

Important Clarifications

What These Workflows ARE

  • Conversation Patterns: Sequences within a single Claude conversation
  • Context Building: Progressive accumulation of understanding
  • Command Sequences: Ordered use of commands for better results
  • Manual Phases: User-controlled project progression

What These Workflows ARE NOT

  • Automated Workflows: No automatic execution or orchestration
  • Parallel Processing: Everything is sequential
  • Persistent Sessions: Context lost between conversations
  • Performance Optimization: No code executes to optimize

Best Practices

Conversation Management

  1. Keep Related Work Together: Don't split related tasks across conversations
  2. Build Context Progressively: Start broad, then focus
  3. Document Key Decisions: Use /sc:save for important points
  4. Manage Conversation Length: Start new conversation if too long

Command Sequencing

  1. Logical Order: Analysis → Design → Implementation → Testing
  2. Context Accumulation: Later commands benefit from earlier context
  3. Appropriate Depth: Match analysis depth to task complexity
  4. Clear Scope: Focus commands on specific areas

Agent Usage

  1. Strategic Activation: Use agents for specific expertise
  2. Avoid Overload: Too many agents can dilute focus
  3. Manual Control: Use @agent- for precise control
  4. Context Layering: Add agents in logical order

Summary

Advanced workflows in SuperClaude are sophisticated conversation patterns that build context progressively within a single Claude Code session. They help generate better outputs through careful command sequencing and context management, but do not involve any actual workflow execution, parallel processing, or automation. Success comes from understanding how to layer context effectively within Claude's conversation scope.