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    d-oit

    goap-agent

    d-oit/goap-agent
    AI & ML

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    SKILL.md

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    About

    Invoke for complex multi-step tasks requiring intelligent planning and multi-agent coordination.

    SKILL.md

    GOAP Agent Skill: Goal-Oriented Action Planning

    Enable intelligent planning and execution of complex multi-step tasks through systematic decomposition, dependency mapping, and coordinated multi-agent execution.

    Always use the plans/ folder for all files.

    Quick Reference

    • Execution Strategies - Detailed guide on parallel, sequential, swarm, hybrid, and iterative execution patterns

    When to Use This Skill

    Use this skill when facing:

    • Complex Multi-Step Tasks: Tasks requiring 5+ distinct steps or multiple specialized capabilities
    • Cross-Domain Problems: Issues spanning multiple areas (storage, API, testing, documentation)
    • Optimization Opportunities: Tasks that could benefit from parallel or hybrid execution
    • Quality-Critical Work: Projects requiring validation checkpoints and quality gates
    • Resource-Intensive Operations: Large refactors, migrations, or architectural changes
    • Ambiguous Requirements: Tasks needing structured analysis before execution

    Core GOAP Methodology

    The GOAP Planning Cycle

    1. ANALYZE → Understand goals, constraints, resources
    2. DECOMPOSE → Break into atomic tasks with dependencies
    3. STRATEGIZE → Choose execution pattern (parallel/sequential/swarm/hybrid/iterative)
    4. COORDINATE → Assign tasks to specialized agents
    5. EXECUTE → Run with monitoring and quality gates
    6. SYNTHESIZE → Aggregate results and validate success
    

    Phase 1: Task Analysis

    Initial Assessment

    ## Task Analysis
    
    **Primary Goal**: [Clear statement of what success looks like]
    
    **Constraints**:
    - Time: [Urgent / Normal / Flexible]
    - Resources: [Available agents, tools, data]
    - Dependencies: [External systems, prerequisites]
    
    **Complexity Level**:
    - Simple: Single agent, <3 steps
    - Medium: 2-3 agents, some dependencies
    - Complex: 4+ agents, mixed execution modes
    - Very Complex: Multiple phases, many dependencies
    
    **Quality Requirements**:
    - Testing: [Unit / Integration / E2E]
    - Standards: [AGENTS.md compliance, formatting, linting]
    - Documentation: [API docs, examples, guides]
    - Performance: [Speed, memory, scalability]
    

    Context Gathering

    1. Codebase Understanding: Use Explore agent to understand relevant code
    2. Past Patterns: Check if similar tasks have been done before
    3. Available Resources: Identify available agents and their capabilities
    4. Current State: Understand starting conditions and existing implementations

    Phase 2: Task Decomposition

    Use the task-decomposition skill to break down the goal:

    ## Task Decomposition: [Task Name]
    
    ### Main Goal
    [Clear statement of primary objective]
    
    ### Sub-Goals
    1. [Component 1] - Priority: P0
       - Success Criteria: [How to verify]
       - Dependencies: [Prerequisites]
       - Complexity: [Low/Medium/High]
    
    2. [Component 2] - Priority: P1
       - Success Criteria: [How to verify]
       - Dependencies: [Component 1]
       - Complexity: [Low/Medium/High]
    
    ### Atomic Tasks
    **Component 1: [Name]**
    - Task 1.1: [Action] (Agent: type, Deps: none)
    - Task 1.2: [Action] (Agent: type, Deps: 1.1)
    
    ### Dependency Graph
    

    Task 1.1 → Task 1.2 → Task 2.1 ↘ Task 1.3 (parallel) → Task 2.2

    
    

    Key Decomposition Principles

    • Atomic: Each task is indivisible and clear
    • Testable: Can verify completion
    • Independent where possible: Minimize dependencies
    • Assigned: Each task maps to an agent capability

    Phase 3: Strategy Selection

    Choose execution strategy based on task characteristics. See execution-strategies.md for detailed guide.

    Quick Strategy Guide

    Strategy When to Use Speed Complexity
    Parallel Independent tasks, time-critical Nx High
    Sequential Dependent tasks, order matters 1x Low
    Swarm Many similar tasks ~Nx Medium
    Hybrid Mixed requirements 2-4x Very High
    Iterative Progressive refinement, convergence Varies Medium

    Decision Tree

    Needs iterative refinement?
      ├─ Yes (until criteria met or converged) → ITERATIVE
      └─ No → Is time critical?
          ├─ Yes → Can tasks run in parallel?
          │   ├─ Yes → PARALLEL
          │   └─ No → SEQUENTIAL (prioritize critical path)
          └─ No → Are tasks similar?
              ├─ Yes (many similar) → SWARM
              ├─ No (mixed) → HYBRID
              └─ Simple linear → SEQUENTIAL
    

    Phase 4: Agent Assignment

    Agent Capability Matrix

    Agent Type Capabilities Best For
    feature-implementer Design, implement, test features New functionality
    debugger Diagnose, fix runtime issues Bug fixes, performance
    test-runner Execute tests, diagnose failures Test validation
    refactorer Improve code quality, structure Code improvements
    code-reviewer Review quality, compliance Quality assurance
    loop-agent Iterative refinement, convergence detection Progressive improvements

    Assignment Principles

    1. Match agent capabilities to task requirements
    2. Balance workload across agents
    3. Consider agent specialization
    4. Plan for quality validation

    Phase 5: Execution Planning

    Create the Execution Plan

    ## Execution Plan: [Task Name]
    
    ### Overview
    - Strategy: [Parallel/Sequential/Swarm/Hybrid/Iterative]
    - Total Tasks: [N]
    - Estimated Duration: [Time]
    - Quality Gates: [N checkpoints]
    
    ### Phase 1: [Phase Name]
    **Tasks**:
    - Task 1: [Description] (Agent: type)
    - Task 2: [Description] (Agent: type)
    
    **Quality Gate**: [Validation criteria]
    
    ### Phase 2: [Phase Name]
    **Tasks**:
    - Task 3: [Description] (Agent: type)
    
    **Quality Gate**: [Validation criteria]
    
    ### Overall Success Criteria
    - [ ] All tasks complete
    - [ ] Quality gates passed
    - [ ] Tests passing
    - [ ] Documentation updated
    
    ### Contingency Plans
    - If Phase 1 fails → [Recovery plan]
    - If tests fail → [Diagnostic approach]
    

    Phase 6: Coordinated Execution

    Parallel Execution

    **Launching parallel agents:**
    - Agent 1 (feature-implementer) → Task A
    - Agent 2 (feature-implementer) → Task B
    - Agent 3 (test-runner) → Task C
    
    **Coordination**:
    - All agents work simultaneously
    - Monitor progress independently
    - Aggregate results when all complete
    

    Sequential Execution

    **Launching sequential agents:**
    Phase 1: Agent 1 (debugger) → Diagnose issue
      ↓ Quality Gate: Root cause identified
    Phase 2: Agent 2 (refactorer) → Apply fix
      ↓ Quality Gate: Tests pass
    Phase 3: Agent 3 (code-reviewer) → Validate
    

    Monitoring During Execution

    • Track agent progress
    • Monitor for failures
    • Validate intermediate results
    • Adjust plan if needed

    Phase 7: Result Synthesis

    Aggregate Results

    ## Execution Summary: [Task Name]
    
    ### ✓ Completed Tasks
    - [Task 1]: Success
    - [Task 2]: Success
    
    ### 📦 Deliverables
    - [File/Feature 1]
    - [File/Feature 2]
    
    ### ✅ Quality Validation
    - Tests: [Pass/Fail] ([coverage]%)
    - Linting: [Pass/Fail]
    - Standards: [Compliant]
    
    ### 📊 Performance Metrics
    - Duration: [actual vs estimated]
    - Efficiency: [parallel speedup if applicable]
    
    ### 💡 Recommendations
    - [Improvement 1]
    - [Improvement 2]
    
    ### 🎓 Lessons Learned
    - [What worked well]
    - [What to improve]
    

    Common GOAP Patterns

    Pattern 1: Research → Implement → Validate

    Phase 1 (Sequential): Research
      - Explore agent → Understand codebase
      - Quality Gate: Architecture documented
    
    Phase 2 (Parallel): Implement
      - feature-implementer (A) → Module 1
      - feature-implementer (B) → Module 2
      - Quality Gate: Implementations complete
    
    Phase 3 (Sequential): Validate
      - test-runner → All tests
      - code-reviewer → Final review
      - Quality Gate: Ready for merge
    

    Pattern 2: Investigate → Diagnose → Fix → Verify

    Phase 1: Investigate
      - debugger → Reproduce issue
      - Quality Gate: Issue reproduced
    
    Phase 2: Diagnose
      - debugger → Root cause analysis
      - Quality Gate: Root cause identified
    
    Phase 3: Fix
      - refactorer → Apply fix
      - Quality Gate: Fix implemented
    
    Phase 4: Verify
      - test-runner → Regression tests
      - Quality Gate: Tests pass
    

    Pattern 3: Audit → Improve → Validate

    Phase 1: Audit
      - code-reviewer → Quality audit
      - Quality Gate: Issues identified
    
    Phase 2 (Swarm): Improve
      - Multiple refactorer agents
      - Work queue: [issue list]
      - Quality Gate: All issues addressed
    
    Phase 3: Validate
      - test-runner → Full test suite
      - code-reviewer → Final check
      - Quality Gate: Quality targets met
    

    Error Handling & Recovery

    Agent Failure Recovery

    **If agent fails:**
    1. Log failure reason
    2. Check quality gate status
    3. Options:
       - Retry same agent (transient error)
       - Assign to different agent (agent issue)
       - Modify task (requirements issue)
       - Escalate to user (blocking issue)
    

    Quality Gate Failure

    **If quality gate fails:**
    1. Identify failing criteria
    2. Diagnose root cause
    3. Options:
       - Re-run previous phase with fixes
       - Adjust quality criteria (if appropriate)
       - Change strategy (e.g., parallel → sequential for debugging)
    

    Blocked Dependencies

    **If dependency blocks progress:**
    1. Identify blocking task
    2. Prioritize unblocking
    3. Options:
       - Execute dependency first (re-order)
       - Remove dependency (refactor plan)
       - Parallel work on independent tasks
    

    Best Practices

    DO:

    ✓ Break tasks into atomic, testable units ✓ Define clear quality gates between phases ✓ Match agent capabilities to task requirements ✓ Monitor progress and validate incrementally ✓ Document decisions and rationale ✓ Learn from execution for future planning ✓ Use parallel execution where safe ✓ Validate dependencies before execution

    DON'T:

    ✗ Create monolithic tasks (break them down) ✗ Skip quality gates (leads to cascading failures) ✗ Assume tasks are independent (verify carefully) ✗ Ignore agent failures (address immediately) ✗ Over-complicate simple tasks (use sequential) ✗ Under-estimate coordination overhead ✗ Forget to aggregate and synthesize results

    Integration with Other Skills

    • task-decomposition: Use for Phase 2 (breaking down complex goals)
    • agent-coordination: Use for Phase 6 (coordinating multiple agents)
    • parallel-execution: Use for parallel strategy implementation
    • loop-agent: Use for iterative refinement strategy implementation
    • All specialized agents (feature-implementer, debugger, test-runner, frontend-design-system, playwright-skill, etc.)

    Quick Example

    Task: Implement authentication system
    
    ## GOAP Plan
    
    ### Phase 1: Analysis (Sequential)
    - goap-agent → Define requirements
    - Quality Gate: Requirements clear
    
    ### Phase 2: Implementation (Parallel)
    - Agent A → User model + database
    - Agent B → Auth middleware
    - Agent C → API endpoints
    - Quality Gate: All components implemented
    
    ### Phase 3: Integration (Sequential)
    - feature-implementer → Wire components together
    - test-runner → Integration tests
    - Quality Gate: Tests pass
    
    ### Phase 4: Validation (Sequential)
    - code-reviewer → Security review
    - Quality Gate: Approved for deployment
    

    Success Metrics

    Planning Quality

    • Clear decomposition with measurable tasks
    • Realistic time estimates
    • Appropriate strategy selection
    • Well-defined quality gates

    Execution Quality

    • Tasks completed as planned
    • Quality gates passed
    • Minimal re-work required
    • Efficient resource utilization

    Learning

    • Document what worked well
    • Identify improvement areas
    • Update patterns for future use
    • Share knowledge with team

    Advanced Topics

    Dynamic Re-Planning

    If during execution:

    • Dependencies change
    • Requirements clarified
    • Blockers discovered
    • Performance issues found

    Then:

    1. Pause execution
    2. Re-analyze with new information
    3. Adjust plan (tasks, dependencies, strategy)
    4. Resume with updated plan

    Optimization Techniques

    • Critical path optimization: Parallelize non-critical-path tasks
    • Resource pooling: Share agents across similar tasks
    • Incremental delivery: Complete and validate phases incrementally
    • Adaptive strategy: Switch strategies based on progress

    Summary

    GOAP enables systematic planning and execution of complex tasks through:

    1. Structured Analysis: Understand goals, constraints, and context
    2. Intelligent Decomposition: Break into atomic, testable tasks
    3. Strategic Execution: Choose optimal execution pattern
    4. Quality Assurance: Validate at checkpoints
    5. Coordinated Agents: Leverage specialized capabilities
    6. Continuous Learning: Improve from each execution

    Use GOAP when facing complex, multi-step challenges requiring coordination, optimization, and quality assurance.

    Repository
    d-oit/do-novelist-ai
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