goap-agent
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
- Codebase Understanding: Use Explore agent to understand relevant code
- Past Patterns: Check if similar tasks have been done before
- Available Resources: Identify available agents and their capabilities
- 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
- Match agent capabilities to task requirements
- Balance workload across agents
- Consider agent specialization
- 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:
- Pause execution
- Re-analyze with new information
- Adjust plan (tasks, dependencies, strategy)
- 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:
- Structured Analysis: Understand goals, constraints, and context
- Intelligent Decomposition: Break into atomic, testable tasks
- Strategic Execution: Choose optimal execution pattern
- Quality Assurance: Validate at checkpoints
- Coordinated Agents: Leverage specialized capabilities
- Continuous Learning: Improve from each execution
Use GOAP when facing complex, multi-step challenges requiring coordination, optimization, and quality assurance.
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