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Initial release: Claude Code Workflow (CCW) v2.0
🚀 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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catlog22
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# Gemini DMS Analysis Templates
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**Specialized templates for Distributed Memory System (DMS) analysis and documentation hierarchy optimization.**
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## Overview
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This document provides DMS-specific analysis templates for architecture analysis, complexity assessment, content strategy, module analysis, and cross-module coordination for intelligent documentation hierarchy management.
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## DMS Architecture Analysis
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### Template Structure
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```bash
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gemini --all-files -p "@{project_patterns} @{module_patterns}
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Context: DMS architecture analysis for @{project_patterns}
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Module structure: @{module_patterns}
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Guidelines: Project standards from @{claude_context}
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Analyze {target} hierarchical documentation structure:
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1. Project complexity assessment (file count, LOC, tech stack diversity)
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2. Module responsibility boundaries and architectural patterns
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3. Cross-module dependencies and integration points
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4. Technology stack analysis and framework usage patterns
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5. Content hierarchy strategy (depth 0-2 classification)
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Provide intelligent classification recommendations with hierarchy mapping."
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```
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### Intelligent Usage Examples
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```python
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# Project structure analysis for DMS hierarchy
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def dms_architecture_analysis(target_path):
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context = build_intelligent_context(
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user_input=f"DMS architecture analysis for {target_path}",
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analysis_type="architecture",
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domains=['dms', 'documentation'],
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tech_stack=detect_project_tech_stack(target_path)
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)
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return f"""
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gemini --all-files -p "@{{{target_path}/**/*}} @{{**/*CLAUDE.md}}
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@{{CLAUDE.md,**/*CLAUDE.md,.claude/*/CLAUDE.md}}
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Analyze project structure for DMS hierarchy optimization:
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- Project complexity: file count, lines of code, technology diversity
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- Module boundaries: logical groupings, responsibility separation
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- Cross-dependencies: integration patterns, shared utilities
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- Documentation needs: complexity-based hierarchy requirements
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- Content differentiation: level-specific focus areas
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- Classification thresholds: >3 files or >300 LOC triggers
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Provide smart hierarchy recommendations with classification rationale."
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"""
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```
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## DMS Complexity Assessment
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### Template Structure
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```bash
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gemini --all-files -p "@{assessment_patterns} @{technology_patterns}
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Context: DMS complexity assessment at @{assessment_patterns}
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Technology stack: @{technology_patterns}
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Guidelines: Classification rules from @{claude_context}
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Evaluate {target} for intelligent DMS classification:
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1. File count analysis and logical grouping assessment
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2. Lines of code distribution and complexity indicators
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3. Technology stack diversity and integration complexity
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4. Cross-module dependencies and architectural coupling
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5. Documentation requirements based on complexity metrics
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Provide classification recommendations with threshold justification."
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```
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### Intelligent Usage Examples
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```python
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# Project complexity evaluation for smart classification
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def dms_complexity_assessment(project_scope):
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context = build_intelligent_context(
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user_input=f"Complexity assessment for {project_scope}",
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analysis_type="quality",
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domains=['dms', 'classification'],
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project_info=analyze_project_structure(project_scope)
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)
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return f"""
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gemini --all-files -p "@{{{project_scope}}} @{{package*.json,requirements.txt,pom.xml}}
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@{{CLAUDE.md,**/CLAUDE.md}}
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Assess project complexity for DMS classification:
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- Single-file detection: 1-2 files → consolidated documentation
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- Simple project: 3-10 files, <800 LOC → minimal hierarchy
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- Medium project: 11-100 files, 800-3000 LOC → selective hierarchy
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- Complex project: >100 files, >3000 LOC → full hierarchy
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- Technology stack: framework diversity impact on documentation needs
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- Integration complexity: cross-module dependency analysis
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Recommend optimal DMS structure with classification thresholds."
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"""
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```
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## DMS Content Strategy
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### Template Structure
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```bash
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gemini --all-files -p "@{content_patterns} @{reference_patterns}
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Context: DMS content strategy for @{content_patterns}
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Reference patterns: @{reference_patterns}
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Guidelines: Content standards from @{claude_context}
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Develop {target} content differentiation strategy:
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1. Level-specific content focus and responsibility boundaries
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2. Content hierarchy optimization and redundancy elimination
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3. Implementation pattern identification and documentation priorities
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4. Cross-level content flow and reference strategies
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5. Quality standards and actionable guideline emphasis
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Provide content strategy with level-specific focus areas."
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```
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### Intelligent Usage Examples
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```python
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# Content strategy for hierarchical documentation
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def dms_content_strategy(hierarchy_levels):
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context = build_intelligent_context(
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user_input=f"Content strategy for {len(hierarchy_levels)} levels",
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analysis_type="quality",
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domains=['dms', 'content', 'hierarchy'],
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levels_info=hierarchy_levels
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)
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return f"""
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gemini --all-files -p "@{{**/*.{{js,ts,jsx,tsx,py,java}}}} @{{**/CLAUDE.md}}
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@{{CLAUDE.md,.claude/*/CLAUDE.md}}
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Develop content differentiation strategy:
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- Depth 0 (Project): Architecture, tech stack, global standards
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- Depth 1 (Module): Module patterns, integration, responsibilities
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- Depth 2 (Implementation): Details, gotchas, specific guidelines
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- Content consolidation: Merge depth 3+ content into depth 2
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- Redundancy elimination: Unique focus per level
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- Non-obvious priority: Essential decisions, actionable patterns
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Provide level-specific content guidelines with focus differentiation."
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"""
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```
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## DMS Module Analysis
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### Template Structure
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```bash
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gemini --all-files -p "@{module_patterns} @{integration_patterns}
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Context: DMS module analysis for @{module_patterns}
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Integration context: @{integration_patterns}
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Guidelines: Module standards from @{claude_context}
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Analyze {target} module-specific documentation needs:
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1. Module responsibility boundaries and architectural role
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2. Internal implementation patterns and conventions
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3. External integration points and dependency management
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4. Module-specific quality standards and best practices
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5. Documentation depth requirements based on complexity
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Provide module documentation strategy with integration focus."
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```
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### Intelligent Usage Examples
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```python
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# Module-specific analysis for targeted documentation
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def dms_module_analysis(module_path):
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context = build_intelligent_context(
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user_input=f"Module analysis for {module_path}",
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analysis_type="architecture",
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domains=['dms', 'module'],
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module_info=analyze_module_structure(module_path)
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)
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return f"""
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gemini --all-files -p "@{{{module_path}/**/*}} @{{**/*{module_path.split('/')[-1]}*}}
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@{{CLAUDE.md,{module_path}/CLAUDE.md}}
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Analyze module for documentation strategy:
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- Module boundaries: responsibility scope, architectural role
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- Implementation patterns: internal conventions, code organization
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- Integration points: external dependencies, API contracts
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- Quality standards: module-specific testing, validation patterns
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- Complexity indicators: >3 files or >300 LOC → dedicated CLAUDE.md
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- Documentation depth: implementation details vs architectural overview
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Recommend module documentation approach with depth justification."
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"""
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```
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## DMS Cross-Module Analysis
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### Template Structure
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```bash
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gemini --all-files -p "@{cross_module_patterns} @{dependency_patterns}
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Context: DMS cross-module analysis for @{cross_module_patterns}
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Dependencies: @{dependency_patterns}
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Guidelines: Integration standards from @{claude_context}
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Analyze {target} cross-module documentation requirements:
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1. Inter-module dependency mapping and communication patterns
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2. Shared utility identification and documentation consolidation
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3. Integration complexity assessment and documentation depth
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4. Cross-cutting concern identification and hierarchy placement
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5. Documentation coordination strategy across module boundaries
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Provide cross-module documentation strategy with integration focus."
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```
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### Intelligent Usage Examples
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```python
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# Cross-module analysis for integration documentation
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def dms_cross_module_analysis(affected_modules):
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context = build_intelligent_context(
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user_input=f"Cross-module analysis for {len(affected_modules)} modules",
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analysis_type="architecture",
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domains=['dms', 'integration', 'modules'],
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modules_info=affected_modules
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)
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module_patterns = ','.join([f"{m}/**/*" for m in affected_modules])
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return f"""
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gemini --all-files -p "@{{{module_patterns}}} @{{**/shared/**/*,**/common/**/*}}
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@{{CLAUDE.md,**/CLAUDE.md}}
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Analyze cross-module integration for documentation:
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- Dependency mapping: module interdependencies, communication flow
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- Shared patterns: common utilities, cross-cutting concerns
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- Integration complexity: >5 modules → enhanced coordination documentation
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- Documentation coordination: avoid redundancy across module boundaries
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- Hierarchy placement: integration patterns at appropriate depth levels
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- Reference strategies: cross-module links and shared guideline access
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Provide integration documentation strategy with coordination guidelines."
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"""
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```
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## DMS Classification Matrix
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### Project Complexity Thresholds
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| Complexity Level | File Count | Lines of Code | Tech Stack | Hierarchy Strategy |
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|------------------|------------|---------------|------------|-------------------|
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| **Single File** | 1-2 files | <300 LOC | 1 technology | Consolidated docs |
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| **Simple** | 3-10 files | 300-800 LOC | 1-2 technologies | Minimal hierarchy |
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| **Medium** | 11-100 files | 800-3000 LOC | 2-3 technologies | Selective hierarchy |
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| **Complex** | >100 files | >3000 LOC | >3 technologies | Full hierarchy |
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### Documentation Depth Strategy
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| Depth Level | Focus Areas | Content Types | Triggers |
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|-------------|-------------|---------------|----------|
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| **Depth 0 (Project)** | Architecture, global standards, tech stack overview | High-level patterns, system design | Always present |
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| **Depth 1 (Module)** | Module patterns, integration points, responsibilities | Interface contracts, module APIs | >3 files or >300 LOC |
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| **Depth 2 (Implementation)** | Implementation details, gotchas, specific guidelines | Code patterns, edge cases | Complex modules |
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## Integration with Intelligent Context
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All DMS templates integrate with @~/.claude/workflows/gemini-intelligent-context.md for:
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- **Smart Project Classification** - Automatic complexity assessment based on project metrics
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- **Module Boundary Detection** - Intelligent identification of logical module groupings
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- **Hierarchy Optimization** - Content differentiation strategies across documentation levels
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- **Cross-Module Coordination** - Integration pattern analysis for documentation coordination
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## Template Usage Guidelines
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1. **Assess Project Complexity First** - Use complexity assessment to determine appropriate hierarchy
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2. **Apply Classification Thresholds** - Follow established metrics for documentation depth decisions
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3. **Coordinate Across Modules** - Use cross-module analysis for integration documentation
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4. **Optimize Content Differentiation** - Ensure unique focus areas for each hierarchy level
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5. **Validate Documentation Strategy** - Check hierarchy alignment with project structure
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These DMS-specific templates enable intelligent documentation hierarchy management and content optimization for distributed memory systems.
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