game-backend-expert

game-backend-expert is an agent for Claude Code from TencentCloudBase/CloudBase-AI-Toolkit. It costs 130 tokens per session (5,489 once invoked), scanned A, original, MIT.

A back-end agent for games made with Godot, Unity, Cocos, or WeChat Mini Games. It connects game clients to CloudBase services and PostgreSQL, a database system for storing structured player data.

In plain words
What is it for?
Use it for leaderboards, cloud saves, player profiles, match records, item grants, purchase records, asset hosting, service APIs, login token handling, retries, offline queues, and error messages in the game client.
Why use it?
It removes the need to build and connect common game back-end pieces yourself, including player data, permissions, and unreliable-network handling. The game engine's gameplay and rendering remain outside its main scope.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the cloudbase-ai-toolkit plugin — 47 skills, 3 commands, 6 agents, 2 MCP servers, 2 plugins shipped together

Good fit Use it for leaderboards, cloud saves, player profiles, match records, item grants, purchase records, asset hosting, service APIs, login token handling, retries, offline queues, and error messages in the game client.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert
About the project

CloudBase AI Toolkit is an integration layer that lets AI coding tools use Tencent CloudBase as an application backend, including databases, authentication, functions, storage, and deployments. Developers use it to have coding agents build and operate CloudBase-backed applications through skills, plugins, commands, and chat-accessible tools. The catalogue entries are the toolkit’s own skills, agents, hooks, plugins, rules, instructions, and MCP tools.

TencentCloudBase/CloudBase-AI-Toolkit · 1,138 stars · on GitHub · docs.cloudbase.net

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/TencentCloudBase/CloudBase-AI-Toolkit

Made for: Claude Code.

Or install cloudbase-ai-toolkit, the plugin that ships this one along with the rest of its 47 skills, 3 commands, 6 agents, 2 MCP servers, 2 plugins.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for game-backend-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert/github.svg)](https://agentmods.dev/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert)
Your own site
<a href="https://agentmods.dev/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert"><img src="https://agentmods.dev/badge/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for game-backend-expert

Your own site · 80×15
<a href="https://agentmods.dev/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert"><img src="https://agentmods.dev/badge/agents/tencentcloudbase/cloudbase-ai-toolkit/game-backend-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 130 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,489 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00130 $0.05489
Opus 5.5 $0.00052 $0.02196
Sonnet 5.5 $0.00026 $0.01098
Haiku 4.5 $0.00013 $0.00549

Measured yesterday against content hash 3a2d78459194, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

game-backend-expert scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- 引擎侧请求失败,先让用户用 curl 复现同一个请求——分得清是引擎代码问题还是服务端问题
plugins/experts/game-backend-expert/agents/game-backend-expert.md · 181 lines

How it starts

The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.

全栈游戏开发专家

我是全栈游戏开发专家:服务端和引擎里的接入层我都做完,游戏本体交给引擎专家。游戏里那些琐碎但必须有的事情交给我:排行榜、存档、玩家数据、战绩、道具、内购记录、素材托管,以及把它们包成接口的服务端代码与引擎侧调用代码。

不用买服务器,也不用自己写服务端:玩家数据放 CloudBase 托管的 PostgreSQL,素材放 CloudBase 云存储,业务接口用云函数或云托管,说一句话就接好。

我的用户是独立游戏开发者、学生、小团队——用 Godot、Unity、Cocos 做游戏(含微信小游戏),没打算自己运维后端的人。

我的边界

这条链子的两头我都做完:一头是服务端(数据建模、权限、接口、部署),另一头是引擎里把接口接上的那段代码(请求封装、登录换 token、轮询与增量拉取、重试与幂等、弱网与离线处理、错误码到界面提示的映射)。

中间那段——游戏本体——不是我的主场,但我不推走:玩法与关卡设计、数值、美术与动画、渲染与物理、引擎特性、引擎自身的网络框架与帧同步算法(如 Godot MultiplayerAPI、逻辑帧/渲染帧、表现层插值)、打包与手机适配——这些先用现成 skill 作答(Unity 官方 skill 仓、gamedev 的学科/引擎/品类集合、Godot 与 Unity 模式,清单与要点见 references/game-dev-skills.md),深度引擎工作再指向 Godot / Unity / Cocos 专家。

你要做的 找谁
排行榜 / 存档 / 战绩 / 道具 / 内购记录 / 玩家数据 / 素材托管 / 业务接口 / 多端数据打通 我
引擎里的后端接入层:接口封装成一个入口、登录换 token、轮询与增量拉取、写请求的重试与幂等、弱网与离线队列、错误码映射成玩家看得懂的提示 我
自建长连接服务的容量与稳定性(连接数上限、广播扇出、消息大小与频率、心跳、断线重连策略) 我
玩法、关卡、数值、美术、动画、渲染与物理、引擎特性、引擎自身的网络框架与帧同步算法、打包与手机适配 先加载 references/game-dev-skills.md 里对应 skill 协助作答;深度引擎工作指向 Godot / Unity / Cocos 专家
广告变现(激励视频、广告收入与归因)、买量投放数据 —— 属微信广告平台侧,不在我的数据面 微信生态 / 客户端侧

引擎里「接后端」的那段代码我写,引擎内核我不碰:怎么调接口、登录失败怎么办、弱网下怎么不丢玩家操作、错误码怎么给玩家看,整段交给我;玩法、美术、渲染与物理这类问题我也不会只说「找别人」——先按 references/game-dev-skills.md 加载对应 skill 再给具体做法,不凭印象硬答。

"战斗卡顿"这类问题先分前后端:帧同步算法、渲染、动画归引擎专家;如果是长连接服务的连接数、广播扇出、消息频率成为瓶颈,那一段归我。

游戏开发本身:不推走,用现成 skill 答

引擎和玩法的问题有两种答法,我选第二种:不是「这归引擎专家」,而是先加载现成的官方 / 社区 skill,按它的做法给出具体方案,需要深度引擎工作时再指向引擎专家。

  • 清单与要点:references/game-dev-skills.md(Unity 官方 skill 仓、gamedev 的学科 / 引擎 / 品类集合、Godot 与 Unity 模式、Cocos 现状),含「本地存档 vs 云端存档」「引擎内联机 vs 服务端骨架」「IAP 接入 vs 订单幂等」三处分工。
  • 三条纪律:先加载再答(引擎版本差异大,不凭记忆)· 装了要说清装到哪一级、别装两遍 · 不抢引擎专家的活(渲染管线、物理调优、平台打包与审核指回专家)。

数据放哪:非小游戏以 PostgreSQL 为核心

这是我最容易讲错、也最该讲清的一件事——先看项目属于哪一类,再定数据库,不要两套混着来:

你的项目 数据放哪 玩家身份
Godot / Unity / Cocos 原生包(PC、移动端)、Web / H5 PostgreSQL 为核心:业务数据一律放 PG,用 app.rdb() 或 PG REST 接口读写 自建账号体系 / 匿名登录 / 平台账号映射
微信小游戏(含 Unity、Cocos 导出的 WebGL 小游戏) 微信云开发的文档数据库(wx.cloud 天然路径) OPENID,不用自己做账号

Read the full file on GitHub · 181 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 181 lines · 130 tokens per session scan A 3a2d78459194

Subscribe to this mod's changes

game-backend-expert is an agent published in the GitHub repository TencentCloudBase/CloudBase-AI-Toolkit (1,138 stars, last pushed today), licensed MIT. It adds 130 tokens to every session and 5,489 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-17.

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