skills.rest
d-o-hub
d-o-hubCOMMUNITY
Explore all skills by this author →
GitHub

goap-planning

Plan minimal action sequences from GOAP state to target state using A* planner.

4|Updated Feb 15, 2026
Search Tags:#automation#planning#state-management#goap#astar#planning-algorithms#action-model
One-click install
npx skills add https://github.com/d-o-hub/chaotic_semantic_memory --skill goap-planning
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: goap-planning
Source: https://github.com/d-o-hub/chaotic_semantic_memory/tree/main/.agents/skills/goap-planning
Command: npx skills add https://github.com/d-o-hub/chaotic_semantic_memory --skill goap-planning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

GOAP planning translates a current world state into a sequence of executable actions that achieve a target state, using well-defined preconditions, effects, and costs.

Core Features & Use Cases

  • Goal-oriented planning: use explicit preconditions and effects to derive a viable action sequence.
  • Cost-aware pathfinding: minimize total effort while satisfying constraints.
  • Use Case: game AI, robotics, and automated workflows where deterministic plans are required.

Quick Start

Provide a current_state, a goal_state, and a list of actions, then run the planner to generate the next executable action sequence.

Frequently Asked Questions about goap-planning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How does GOAP planning generate an executable action sequence from a current state?▼

GOAP planning generates an executable action sequence by applying an A* planner to find a minimal cost path from the current world state to a target state using actions defined by preconditions, effects, and costs.

How do I implement cost-aware pathfinding for automated workflows using action models?▼

To implement cost-aware pathfinding, you model actions with preconditions, effects, and costs via an action model, then compute the path with an A* planner to minimize total effort while satisfying workflow constraints.

Can I use GOAP planning for game AI and robotics state management?▼

Yes, GOAP planning is designed for game AI, robotics, and automated workflows where deterministic, cost-aware action plans are required to transition between states.

What do I need to provide to run a GOAP planner for goal-oriented planning?▼

To run a GOAP planner, you need to provide a current state, a target goal state, and a list of actions, which the planner uses to generate the next executable action sequence.

How does the planner update the world state after executing an action?▼

The planner updates the world state by persisting the next computed action, executing it, and then applying its effects to ensure deterministic state transitions after each step.

What are the limitations of using A* planner patterns for state management?▼

The A* planner pattern requires explicitly defined preconditions, effects, and costs for every action, meaning it is limited to deterministic environments where state transitions can be precisely modeled.

Related Skills

Explore More Software Engineering Skills→
XioaqiZhangXioaqiZhang

algorithm-animation

Generate Remotion projects that animate sorting, searching, tree, and graph algorithms.

Community
Intermediate
aslaiiaslaii

gsd-progress

Summarize project progress and route to the next action with deterministic logic.

Community
Advanced
AesopScottAesopScott

skip-reviewer

Skip re-review processes for validated model paths within the Trust harness.

Community
Intermediate
ftnilssonftnilsson

AI & Navigation

Implement game AI in Godot 4 with NavigationServer pathfinding and state machines.

Community
Intermediate