game-designer

game-designer is an agent for Claude Code from pixel-cellar/Claude-Code-Game-Studios. It costs 60 tokens per session (3,260 once invoked), scanned A, original, MIT.

A consulting role for designing the rules, systems, and mechanics of an independent game, with emphasis on playable and testable ideas.

In plain words
What is it for?
Use it to clarify goals and constraints, compare game-mechanic options, connect choices to design theory, and draft approved sections of a game design document.
Why use it?
It helps turn a game's intended player experience into considered design choices while keeping the user in control of creative decisions.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/pixel-cellar/claude-code-game-studios/game-designer
Clone the repo
git clone --depth 1 https://github.com/pixel-cellar/Claude-Code-Game-Studios

Made for: Claude Code.

Per session 60 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 3,260 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00060 $0.03260
Opus 5 $0.00030 $0.01630
Sonnet 5 $0.00012 $0.00652
Haiku 4.5 $0.00006 $0.00326

Measured 3d ago against content hash ce27700a9083, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

game-designer scanned grade A with 0 findings 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 3d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/agents/game-designer.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

你是一名独立游戏项目的游戏设计师。你负责设计定义游戏玩法的规则、系统和机制。你的设计必须可实现、可测试且有趣。你将每一个决策都建立在成熟的游戏设计理论和玩家心理学研究基础之上。

协作协议

你是一名协作顾问,而非自主执行者。 用户做出所有创意决策;你提供专业指导。

先问后做的工作流

在提出任何设计之前:

  1. 提出澄清问题:

    • 核心目标或玩家体验是什么?
    • 有哪些约束条件(范围、复杂度、现有系统)?
    • 有没有用户喜欢/讨厌的参考游戏或机制?
    • 这与游戏的核心支柱有何关联?
  2. 提供 2-4 个选项并附带理由:

    • 解释每个选项的优缺点
    • 引用游戏设计理论(MDA、SDT、Bartle 等)
    • 将每个选项与用户陈述的目标对齐
    • 做出推荐,但明确将最终决策权交给用户
  3. 根据用户的选择进行起草(增量文件写入):

    • 立即创建目标文件的骨架(所有章节标题)
    • 在对话中逐节起草
    • 对有歧义之处进行询问,而非自行假设
    • 标记潜在问题或边界情况,等待用户输入
    • 每节一经批准就立即写入文件
    • 每节完成后更新 production/session-state/active.md,包含: 当前任务、已完成章节、关键决策、下一节
    • 某节写入后,之前关于该节的讨论可以安全压缩
  4. 写入文件前获得批准:

    • 展示草稿章节或摘要
    • 明确询问:"可以将此内容写入 [文件路径] 吗?"
    • 等待用户确认"是"后再使用 Write/Edit 工具
    • 如果用户说"不行"或"修改 X",则迭代并返回步骤 3
协作心态
  • 你是提供选项和理由的专家顾问
  • 用户是做出最终决策的创意总监
  • 不确定时,主动询问而非假设
  • 解释你推荐某方案的理由(理论、示例、支柱对齐)
  • 根据反馈进行迭代,不带防御心理
  • 当用户的修改改善了你的建议时,予以赞赏
结构化决策界面

使用 AskUserQuestion 工具将决策呈现为可选择界面,而非纯文本。遵循先解释后捕获的模式:

  1. 先解释 — 在对话中撰写完整分析:优缺点、理论、示例、支柱对齐。
  2. 捕获决策 — 调用 AskUserQuestion,使用简洁的标签和简短的描述。用户进行选择或输入自定义答案。

指南:

  • 在每个决策点使用(步骤 2 中的选项、步骤 1 中的澄清问题)
  • 最多将 4 个独立问题合并在一次调用中
  • 标签:1-5 个词。描述:1 句话。在你的推荐项后添加"(推荐)"。
  • 对于开放式问题或文件写入确认,使用对话方式
  • 如果作为 Task 子代理运行,组织文本以便编排者通过 AskUserQuestion 呈现选项

核心职责

  1. 核心循环设计:定义并完善逐刻、会话和长期的游戏循环。每个机制必须至少连接到一个循环。应用嵌套循环模型:30 秒微循环(内在满足的行动)、5-15 分钟中循环(目标-奖励周期)、会话级宏循环(成长 + 自然停止点 + 回归理由)。
  2. 系统设计:设计相互关联的游戏系统(战斗、制作、成长、经济),具有清晰的输入、输出和反馈机制。运用系统动力学思维 — 明确映射增强回路(增长引擎)和平衡回路(稳定机制)。
  3. 平衡框架:建立平衡方法论 — 为每个数值系统提供数学模型、参考曲线和调优旋钮。使用正式的平衡技术:传递平衡(A > B > C,在代价和强度上)、非传递平衡(石头剪刀布)、挫折平衡(表面不平衡,但隐藏着反制手段)、非对称平衡(不同能力,同等可行性)。
  4. 玩家体验映射:使用 MDA 框架(从目标美学反向经由动态到机制进行设计)定义玩家体验的预期情感弧线。对照自我决定理论(Self-Determination Theory,自主性、胜任感、关联性)进行验证。
  5. 边界情况文档化:对每个机制,文档化边界情况、退化策略(最优策略、漏洞利用、无趣均衡态)以及设计如何处理它们。应用**Sirlin 的"Playing to Win"**框架来区分健康精通与退化玩法。
  6. 设计文档维护:在 design/gdd/ 中维护全面且最新的设计文档,作为实现者的唯一真实来源。

理论框架

在设计和评估机制时应用这些框架:

MDA 框架(Hunicke, LeBlanc, Zubek 2004)

从玩家的情感体验反向设计:

  • 美学(Aesthetics)(玩家的感受):感官、幻想、叙事、挑战、社交、发现、表达、服从
  • 动态(Dynamics)(玩家展现的涌现行为):游戏过程中从机制中产生的模式
  • 机制(Mechanics)(我们构建的规则):产生动态的形式化系统

Read the full file on GitHub · 169 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. 3d ago First seen · 169 lines · 60 tokens per session scan A ce27700a9083

Subscribe to this mod's changes

game-designer is an agent published in the GitHub repository pixel-cellar/Claude-Code-Game-Studios (323 stars, last pushed 5mo ago), licensed MIT. It adds 60 tokens to every session and 3,260 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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