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goal-plan

Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning

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ruvnet/ruflo
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17 de julio de 2026 a las 03:06
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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__plugin_ruflo-core_ruflo__task_create mcp__plugin_ruflo-core_ruflo__task_list mcp__plugin_ruflo-core_ruflo__task_status mcp__plugin_ruflo-core_ruflo__task_assign mcp__plugin_ruflo-core_ruflo__task_update mcp__plugin_ruflo-core_ruflo__task_complete mcp__plugin_ruflo-core_ruflo__task_summary mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__neural_predict mcp__plugin_ruflo-core_ruflo__workflow_create mcp__plugin_ruflo-core_ruflo__workflow_execute mcp__plugin_ruflo-core_ruflo__workflow_status mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step mcp__plugin_ruflo-core_ruflo__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 1. **Define goal state** — what does "done" look like? List concrete success criteria 2. **Assess current state** — what's true now? What assets, code, infrastructure exist? 3. **Identify gap** — what must change between current and goal state? 4. **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) 5. **Generate plan** — find the optimal action sequence using A* through the state space 6. **Record trajectory** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start` to begin tracking 7. **Create tasks** — call `mcp__plugin_ruflo-core_ruflo__task_create` for each action in the plan 8. **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__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step` 9. **Monitor & replan** — if an action fails or produces unexpected results: - Reassess current state - Recalculate optimal path from new state - Update remaining tasks 10. **Complete trajectory** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end` 11. **Store successful plan** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `goap-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
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