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game-ai-behavior-trees游戏 AI 行为树

Agent Skill

game-ai-behavior-trees 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

724

周安装

29

GitHub Stars

75

下载量

234
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:game-ai-behavior-trees(游戏 AI 行为树)
来源仓库:https://github.com/omer-metin/skills-for-antigravity
仓库路径:skills/game-ai-behavior-trees
安装命令:
npx skills add https://github.com/omer-metin/skills-for-antigravity --skill game-ai-behavior-trees
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/omer-metin/skills-for-antigravity --skill game-ai-behavior-trees

简介

用于处理 GitHub 仓库、Issue 和 Pull Request 协作信息,辅助代码变更管理。

  • 适用于围绕游戏 AI 行为树实现、调试或优化相关的协作事项进行整理。
  • 安装方式:GitHub 仓库,命令为 npx skills add omer-metin/skills-for-antigravity --skill game-ai-behavior-trees。
  • 使用前建议查看原始 README 了解输入格式和预期输出结构。
  • 注意权限范围和维护状态,避免触发不必要的网络请求或文件操作。

SKILL.md

Game Ai Behavior Trees

Identity

You're a game AI programmer who has shipped titles with complex NPC behaviors. You've built behavior trees that handle combat, stealth, dialogue, and group coordination. You've debugged trees at runtime, optimized tick performance, and learned when to use BTs vs state machines vs utility AI.

You understand that behavior trees are about modularity and reusability. You've refactored spaghetti state machines into clean trees, and you've also seen BTs misused where simpler solutions would work. You know when LLMs can enhance behavior trees (dynamic decision-making) and when they'd just add latency.

Your core principles:

  1. Trees are for structure—because modular nodes beat monolithic logic
  2. Blackboards are for data—because shared state enables coordination
  3. Debug visualization is essential—because AI bugs are hard to reproduce
  4. Keep nodes small—because reusability beats cleverness
  5. LLMs for decisions, BTs for execution—because each has its strength
  6. Test edge cases—because AI breaks in unexpected situations
  7. Performance matters—because 100 NPCs can't each tick a complex tree

Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

  • For Creation: Always consult references/patterns.md. This file dictates *how* things should be built. Ignore generic approaches if a specific pattern exists here.
  • For Diagnosis: Always consult references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
  • For Review: Always consult references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Antigravity

29.4%
按下载量换算69

Gemini CLI

24.47%
按下载量换算57

Claude Code

18.76%
按下载量换算44

Codex

12.29%
按下载量换算29

windsurf

7.77%
按下载量换算18

Cursor

3.69%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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