ix-search

Implement A*, Q*, Minimax, MCTS, BFS, and DFS search algorithms for pathfinding and games.

Updated Mar 12, 2026

Search Tags:#algorithm #pathfinding #A*#MCTS #Minimax

Ready to run

npx skills add https://github.com/GuitarAlchemist/ix --skill ix-search

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ix-search
Source: https://github.com/GuitarAlchemist/ix/tree/main/.claude/skills/ix-search
Command: npx skills add https://github.com/GuitarAlchemist/ix --skill ix-search

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

ix-search addresses the problem of efficient search and pathfinding across complex domains, whether it's for games, robotics, or optimizing decisions in a dynamic environment.

Core Features & Use Cases

Algorithm Selection: Offers algorithms such as A*, Q*, MCTS, Minimax, BFS/DFS, catering to a variety of search scenarios.
Optimal Path Finding: Utilizes heuristic search to find the shortest path to a known goal, or MCTS for larger state spaces with probabilistic outcomes.
Use Case: An example could be implementing game AI using the Minimax algorithm to provide an optimal strategy in turn-based games like chess or Go.

Quick Start

Utilize ix-search to calculate an optimal path for a robot in a grid, considering various obstacle placements and cost factors.

Frequently Asked Questions about ix-search

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

FAQPage Schema

How do I find the optimal path for a robot in a grid with obstacles?▼

To find the optimal path for a robot in a grid with obstacles, you can use heuristic search algorithms like A* that calculate the shortest route to a known goal while minimizing computation cost.

What is the best way to implement AI for turn-based games like chess?▼

The best way to implement AI for turn-based games like chess is using the Minimax algorithm to evaluate game states and provide an optimal strategy against opponent moves.

When should I use MCTS instead of A* for pathfinding problems?▼

You should use MCTS instead of A* for pathfinding when dealing with larger state spaces that have probabilistic outcomes, as MCTS handles uncertain dynamics better than admissible heuristic approaches.

Can I use BFS and DFS algorithms for general search tasks in dynamic environments?▼

Yes, you can use BFS and DFS algorithms for general search tasks in dynamic environments, as they provide foundational traversal strategies alongside advanced methods like A* and Minimax for diverse domains.

Does this search algorithm solution handle probabilistic goals effectively?▼

Yes, this search algorithm solution handles probabilistic goals effectively by utilizing Monte Carlo Tree Search (MCTS) to evaluate larger state spaces and optimize decisions where outcomes are uncertain.

Why does algorithm selection matter for minimizing computation cost in pathfinding?▼

Algorithm selection matters for minimizing computation cost in pathfinding because different scenarios require tailored approaches—A* for known goals with admissible heuristics, MCTS for probabilistic spaces—ensuring optimal strategy without wasted resources.