🚀 Revolutionary AI-powered development workflow orchestration system ## 🔥 Core Innovations - **Document-State Separation**: Markdown for planning, JSON for execution state - **Progressive Complexity Management**: Level 0-2 adaptive workflow depth - **5-Agent Orchestration**: Specialized AI agents with context preservation - **Session-First Architecture**: Auto-discovery and state inheritance ## 🏗️ Key Features - Intelligent workflow orchestration (Simple/Medium/Complex patterns) - Real-time document-state synchronization with conflict resolution - Hierarchical task management with 3-level JSON structure - Gemini CLI integration with 12+ specialized templates - Comprehensive file output generation for all workflow commands ## 📦 Installation Remote one-liner installation: ``` iex (iwr -useb https://raw.githubusercontent.com/catlog22/Claude-CCW/main/install-remote.ps1) ``` ## 🎯 System Architecture 4-layer intelligent development architecture: 1. Command Layer - Smart routing and version management 2. Agent Layer - 5 specialized development agents 3. Workflow Layer - Gemini templates and task orchestration 4. Memory Layer - Distributed documentation and auto-sync 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
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name, description
| name | description |
|---|---|
| Agent Workflow Coordination | Core coordination principles for multi-agent development workflows |
System Reference
Complete Architecture: @~/.claude/workflows/core-principles.md
This document defines essential coordination principles between agents. For complete system architecture, file structures, commands, and implementation details, refer to the unified workflow system principles.
Core Agent Coordination Principles
Planning First Principle
Purpose: Thorough upfront planning reduces risk, improves quality, and prevents costly rework.
Mandatory Triggers: Planning is required for tasks spanning:
-
3 modules or components
-
1000 lines of code
- Architectural changes
- High-risk dependencies
Key Deliverables:
IMPL_PLAN.md: Central planning document for all complexity levels- Progressive file structure based on task complexity
.summaries/: Automated task completion documentation.chat/: Context analysis sessions from planning phase
TodoWrite Coordination Rules
- TodoWrite FIRST: Always create TodoWrite entries before agent execution begins.
- Real-time Updates: Status must be marked
in_progressorcompletedas work happens. - Agent Coordination: Each agent is responsible for updating the status of its assigned todo.
- Progress Visibility: Provides clear workflow state visibility to stakeholders.
- Single Active: Only one todo should be
in_progressat any given time. - Checkpoint Safety: State is saved automatically after each agent completes its work.
- Interrupt/Resume: The system must support full state preservation and restoration.
Implementation Prerequisites Principle
Deliverable Validation: Code modification agents can only execute when proper planning deliverables exist.
Required Artifacts Before Implementation (at least one must exist):
IMPL_PLAN.md: Must contain detailed implementation strategy.chat/sessions: Context analysis supporting planning decisions- Task definitions: JSON task files with clear acceptance criteria
- Complexity assessment: Validated task complexity and scope
Validation Protocol:
FUNCTION validate_implementation_prerequisites():
artifacts_found = 0
IF exists("IMPL_PLAN.md") AND valid_content("IMPL_PLAN.md"):
artifacts_found += 1
IF exists(".chat/") AND NOT empty_directory(".chat/"):
artifacts_found += 1
IF validate_task_definitions():
artifacts_found += 1
IF has_complexity_assessment():
artifacts_found += 1
IF artifacts_found == 0:
BLOCK_IMPLEMENTATION("No planning artifacts found - at least one required")
IF artifacts_found < 2:
WARN_IMPLEMENTATION("Limited planning context - recommend additional artifacts")
RETURN READY_FOR_IMPLEMENTATION
END FUNCTION
Core Workflow Process
TodoWrite Creation -> Context Collection -> Implementation -> Quality Assurance -> State Update
Interrupt & Resume Protocol
Checkpoint Strategy Flow:
Agent Completes -> Save State (Todo + Context) -> Check for Interrupt Signal -> Continue or Stop
State Components for Resume:
- TodoWrite current state
- Agent output chain
- Accumulated context
- Planning documents
.chat/analysis history
Agent Selection Logic
FUNCTION select_agent_for_task(task_complexity):
CASE task_complexity:
WHEN 'Research/Analysis':
RETURN "General-Purpose" // For research, file analysis
WHEN 'Simple Implementation':
RETURN "Code Developer" // For implementation, TDD, algorithms
WHEN 'Complex Features (3+ components)':
RETURN ["Action Planning", "Code Developer", "Code Review"] // Multi-stage agent chain
WHEN 'Full Lifecycle':
RETURN "Boomerang" // For full workflow orchestration
WHEN 'Post-Implementation':
RETURN "Code Review" // For quality validation, security, compliance
END FUNCTION
Agent Output Standards
Action Planning Agent:
PLAN_SUMMARY: [One-line summary]
STEPS: [Numbered deliverables]
SUCCESS_CRITERIA: [Measurable standards]
TODOWRITE_ENTRIES: [TodoWrite items created for each stage/subtask]
Code Developer Agent:
PREREQUISITE_VALIDATION: [IMPL_PLAN.md and .chat/ sessions verified]
IMPLEMENTATION_SUMMARY: [What was built]
FILES_MODIFIED: [File list with changes]
CONTEXT_REFERENCES: [Links to supporting .chat/ analysis]
TODOWRITE_UPDATES: [Progress status updates made during implementation]
READY_FOR_REVIEW: [YES/NO with reason]
Code Review Agent:
REVIEW_STATUS: [PASS/ISSUES_FOUND/CRITICAL_ISSUES]
QUALITY_SCORE: [1-10]
TODOWRITE_COMPLETION: [Tasks marked as completed after validation]
RECOMMENDATION: [APPROVE/FIX_REQUIRED/REVISION_NEEDED]