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- Remove detailed progress views (Total Tasks: X, Completed: Y %) from all templates - Simplify TODO_LIST.md structure by removing Progress Overview sections - Remove stats tracking from session-management-principles.json schema - Eliminate progress format and calculation logic from context command - Remove percentage-based progress displays from action-planning-agent - Simplify vibe command coordination by removing detailed task counts - Focus on essential JSON state changes rather than UI progress metrics 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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6.6 KiB
Agent Orchestration Patterns
Core Agent Coordination Features
- Gemini Context Analysis: MANDATORY context gathering before any agent execution
- Context-Driven Coordination: Agents work with comprehensive codebase understanding
- Dynamic Agent Selection: Choose agents based on discovered context and patterns
- Continuous Context Updates: Refine understanding throughout agent execution
- Cross-Agent Context Sharing: Maintain shared context state across all agents
- Pattern-Aware Execution: Leverage discovered patterns for optimal implementation
- Quality Gates: Each Agent validates input and ensures output standards
- Error Recovery: Graceful handling of Agent coordination failures
Workflow Implementation Patterns
Simple Workflow Pattern
Flow: Gemini Context Analysis → TodoWrite Creation → Context-Aware Implementation → Review
1. MANDATORY Gemini Context Analysis:
- Analyze target files and immediate dependencies
- Discover existing patterns and conventions
- Identify utilities and libraries to use
- Generate context package for agents
2. TodoWrite Creation (Context-informed):
- "Execute Gemini context analysis"
- "Implement solution following discovered patterns"
- "Review against codebase standards"
- "Complete task with context validation"
3. Context-Aware Implementation:
Task(code-developer): Implementation with Gemini context package
Input: CONTEXT_PACKAGE, PATTERNS_DISCOVERED, CONVENTIONS_IDENTIFIED
Output: SUMMARY, FILES_MODIFIED, TESTS, VERIFICATION
4. Context-Aware Review:
Task(code-review-agent): Review with codebase standards context
Input: CONTEXT_PACKAGE, IMPLEMENTATION_RESULTS
Output: STATUS, SCORE, ISSUES, RECOMMENDATIONS
Resume Support: Load todos + full context state from checkpoint
Medium Workflow Pattern
Flow: Comprehensive Gemini Analysis → TodoWrite → Multi-Context Implementation → Review
1. MANDATORY Comprehensive Gemini Context Analysis:
- Analyze feature area and related components
- Discover cross-file patterns and architectural decisions
- Identify integration points and dependencies
- Generate comprehensive context packages for multiple agents
2. TodoWrite Creation (Context-driven, 5-7 todos):
- "Execute comprehensive Gemini context analysis"
- "Coordinate multi-agent implementation with shared context"
- "Implement following discovered architectural patterns"
- "Validate against existing system patterns", "Review", "Complete"
3. Multi-Context Implementation:
Task(code-developer): Implementation with comprehensive context
Input: CONTEXT_PACKAGES, ARCHITECTURAL_PATTERNS, INTEGRATION_POINTS
Update context as new patterns discovered
4. Context-Aware Review:
Task(code-review-agent): Comprehensive review with system context
Input: FULL_CONTEXT_STATE, IMPLEMENTATION_RESULTS, PATTERN_COMPLIANCE
Verify against discovered architectural patterns
Resume Support: Full context state + pattern discovery restoration
Complex Workflow Pattern
Flow: Deep Gemini Analysis → TodoWrite → Orchestrated Multi-Agent → Review → Iterate (max 2)
1. MANDATORY Deep Gemini Context Analysis:
- System-wide architectural understanding
- Deep pattern analysis across entire codebase
- Integration complexity assessment
- Multi-agent coordination requirements discovery
- Risk pattern identification
2. TodoWrite Creation (Context-orchestrated, 7-10 todos):
- "Execute deep system-wide Gemini analysis"
- "Orchestrate multi-agent coordination with shared context"
- "Implement with continuous context refinement"
- "Validate against system architectural patterns", "Review", "Iterate", "Complete"
3. Orchestrated Multi-Agent Implementation:
Multiple specialized agents with shared deep context
Input: SYSTEM_CONTEXT, ARCHITECTURAL_PATTERNS, RISK_ASSESSMENT
Continuous Gemini context updates throughout execution
Cross-agent context synchronization
4. Deep Context Review & Iteration Loop (max 2 iterations):
Task(code-review-agent): Production-ready review with full system context
If CRITICAL_ISSUES found: Re-analyze context and coordinate fixes
Continue until no critical issues or max iterations reached
Context Validation: Verify deep context analysis maintained throughout
Resume Support: Full context state + iteration tracking + cross-agent coordination
Workflow Characteristics by Pattern
| Pattern | Context Analysis | Agent Coordination | Iteration Strategy |
|---|---|---|---|
| Complex | Deep system-wide Gemini analysis | Multi-agent orchestration with shared context | Multiple rounds with context refinement |
| Medium | Comprehensive multi-file analysis | Context-driven coordination | Single thorough pass with pattern validation |
| Simple | Focused file-level analysis | Direct context-aware execution | Quick context validation |
Context-Driven Task Invocation Examples
# Gemini Context Analysis (Always First)
gemini "Analyze authentication patterns in codebase - identify existing implementations,
conventions, utilities, and integration patterns"
# Context-Aware Research Task
Task(subagent_type="general-purpose",
prompt="Research authentication patterns in codebase",
context="[GEMINI_CONTEXT_PACKAGE]")
# Context-Informed Implementation Task
Task(subagent_type="code-developer",
prompt="Implement email validation function following discovered patterns",
context="PATTERNS: [pattern_list], UTILITIES: [util_list], CONVENTIONS: [conv_list]")
# Context-Driven Review Task
Task(subagent_type="code-review-agent",
prompt="Review authentication service against codebase standards and patterns",
context="STANDARDS: [discovered_standards], PATTERNS: [existing_patterns]")
# Cross-Agent Context Sharing
Task(subagent_type="code-developer",
prompt="Coordinate with previous agent results using shared context",
context="PREVIOUS_CONTEXT: [agent_context], SHARED_STATE: [context_state]")
Gemini Context Integration Points
Pre-Agent Context Gathering
# Always execute before agent coordination
gemini "Comprehensive analysis for [task] - discover patterns, conventions, and optimal approach"
During-Agent Context Updates
# Continuous context refinement
gemini "Update context understanding based on agent discoveries in [area]"
Cross-Agent Context Synchronization
# Ensure context consistency across agents
gemini "Synchronize context between [agent1] and [agent2] work on [feature]"