- name
- goal-plan
- description
- Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning
- argument-hint
- <goal-description>
- allowed-tools
- mcp__claude-flow__task_create mcp__claude-flow__task_list mcp__claude-flow__task_status mcp__claude-flow__task_assign mcp__claude-flow__task_update mcp__claude-flow__task_complete mcp__claude-flow__task_summary mcp__claude-flow__memory_store mcp__claude-flow__memory_search mcp__claude-flow__neural_predict mcp__claude-flow__workflow_create mcp__claude-flow__workflow_execute mcp__claude-flow__workflow_status mcp__claude-flow__hooks_intelligence_trajectory-start mcp__claude-flow__hooks_intelligence_trajectory-step mcp__claude-flow__hooks_intelligence_trajectory-end Bash Read Write Edit
Goal Plan
Create and execute intelligent plans using Goal-Oriented Action Planning (GOAP).
When to use
When you have a complex objective that requires multiple steps, has dependencies between steps, and may need adaptive replanning as conditions change.
Steps
- Define goal state — what does "done" look like? List concrete success criteria
- Assess current state — what's true now? What assets, code, infrastructure exist?
- Identify gap — what must change between current and goal state?
- Inventory actions — list available actions with:
- Preconditions (what must be true before this action) - Effects (what becomes true after this action) - Cost estimate (time, complexity, risk)
- Generate plan — find the optimal action sequence using A* through the state space
- Record trajectory — call
mcp__claude-flow__hooks_intelligence_trajectory-startto begin tracking - Create tasks — call
mcp__claude-flow__task_createfor each action in the plan - Execute — work through tasks in dependency order:
- Before each action: verify preconditions still hold - After each action: verify effects achieved - Record each step via mcp__claude-flow__hooks_intelligence_trajectory-step
- Monitor & replan — if an action fails or produces unexpected results:
- Reassess current state - Recalculate optimal path from new state - Update remaining tasks
- Complete trajectory — call
mcp__claude-flow__hooks_intelligence_trajectory-end - Store successful plan — call
mcp__claude-flow__memory_storewith namespacegoap-plans
Plan output format
Goal: [concrete objective]
Current State: [key facts]
Plan Cost: [estimated effort]
Steps:
1. [action] — precondition: [X], effect: [Y], cost: [Z]
2. [action] — precondition: [Y], effect: [W], cost: [Z]
...
Risk Factors: [what could force a replan]
Fallback: [alternative approach if primary path fails]Replanning triggers
- Action fails (precondition no longer met)
- Unexpected side effects detected
- New information changes goal definition
- Cost exceeds threshold
- External dependency becomes unavailable