# mcts-gen

> mcts-gen — akuroiwa-mcts-gen. Use this tool when you need to implement a generic Monte Carlo Tree Search (MCTS) framework for decision-making and game-playing tasks, leveraging AI-driven policy and value functions to solve complex problems. It takes in game state and policy/value networks as inputs and outputs optimal moves or actions. Ideal for use cases like game playing, planning, and optimization, where exploration and exploitation trade-offs are crucial.

Canonical page: https://skillsregistry.net/skills/akuroiwa-mcts-gen  
JSON: https://api.skillsregistry.net/v1/skills/akuroiwa-mcts-gen

## Description

Generic MCTS Framework with AI-driven Policy/Value

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** GPL-3.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/akuroiwa/mcts-gen)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "akuroiwa-mcts-gen"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/akuroiwa-mcts-gen` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/akuroiwa-mcts-gen/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt