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.
npx skills add pixel-cellar/Claude-Code-Game-Studios --skill map-systemsgit clone --depth 1 https://github.com/pixel-cellar/Claude-Code-Game-StudiosWrote 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.
[](https://agentmods.dev/skills/pixel-cellar/claude-code-game-studios/map-systems)<a href="https://agentmods.dev/skills/pixel-cellar/claude-code-game-studios/map-systems"><img src="https://agentmods.dev/badge/skills/pixel-cellar/claude-code-game-studios/map-systems/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.
<a href="https://agentmods.dev/skills/pixel-cellar/claude-code-game-studios/map-systems"><img src="https://agentmods.dev/badge/skills/pixel-cellar/claude-code-game-studios/map-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.03069 |
| Opus 5.5 | $0.00013 | $0.01228 |
| Sonnet 5.5 | $0.00006 | $0.00614 |
| Haiku 4.5 | $0.00003 | $0.00307 |
Grade A, and why
map-systems 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
当此技能被调用时：
1. 解析参数
两种模式：
- 无参数：
/map-systems— 运行完整的拆解工作流（阶段 1-5）以创建或更新系统索引。 next：/map-systems next— 从索引中选择最高优先级的未设计系统并交接给/design-system（阶段 6）。
2. 阶段 1：读取概念（必需上下文）
读取游戏概念和任何已有的设计工作。这为系统拆解提供了原始材料。
必需：
- 读取
design/gdd/game-concept.md— 如果缺失则明确报错退出："在
design/gdd/game-concept.md未找到游戏概念。请先运行/brainstorm创建一个，然后再回来将其拆解为系统。"
可选（如果存在则读取）：
- 读取
design/gdd/game-pillars.md— 游戏支柱约束优先级和范围 - 读取
design/gdd/systems-index.md— 如果存在，从上次中断处继续（更新，而非从头重建） - Glob
design/gdd/*.md— 检查哪些系统 GDD 已经存在
如果系统索引已存在：
- 读取并向用户展示当前状态
- 使用
AskUserQuestion询问： "系统索引已存在，包含 [N] 个系统（[M] 个已设计，[K] 个未开始）。您希望做什么？"- 选项："更新索引中的新系统"、"设计下一个未设计系统"、"审查并修订优先级"
3. 阶段 2：系统枚举（协作式）
提取并识别游戏需要的所有系统。这是本技能的核心创意环节 — 它需要人工判断，因为概念文档很少明确列举每个系统。
步骤 2a：提取显式系统
扫描游戏概念中直接提及的系统和机制：
- 核心机制部分（最明确）
- 核心循环部分（暗示驱动每层循环的系统）
- 技术考量部分（联网、程序化生成等）
- MVP 定义部分（必需功能 = 必需系统）
步骤 2b：识别隐式系统
对于每个显式系统，识别它所暗示的隐藏系统。游戏需要的系统总是比概念文档中提到的多。使用以下推理模式：
- "背包" 暗示：物品数据库、装备槽、重量/容量规则、背包 UI、物品序列化以实现存读档
- "战斗" 暗示：伤害计算、生命值系统、命中检测、状态效果、敌人 AI、战斗 UI（血条、伤害数字）、死亡/重生
- "开放世界" 暗示：流式加载/分块、LOD (Level of Detail) 系统、快速旅行、地图/小地图、兴趣点追踪、世界状态持久化
- "多人游戏" 暗示：网络层、大厅/匹配、状态同步、反作弊、网络 UI（延迟、玩家列表）
- "制作" 暗示：配方数据库、材料收集、制作 UI、成功/失败机制、配方发现/学习
- "对话" 暗示：对话树系统、对话 UI、选择追踪、NPC 状态管理、本地化钩子
- "成长" 暗示：经验值系统、升级机制、技能树、解锁追踪、成长 UI、成长存档数据
在对话中解释为什么需要每个隐式系统（附示例）。
步骤 2c：用户审核
按类别组织展示枚举结果。对于每个系统，展示：
- 名称
- 类别
- 简要描述（一句话）
- 是显式的（来自概念）还是隐式的（推理得出）
然后使用 AskUserQuestion 收集反馈：
- "此列表中是否缺少系统？"
- "是否有需要合并或拆分的系统？"
- "是否有此游戏不需要的系统？"
迭代直到用户批准枚举结果。
4. 阶段 3：依赖映射（协作式）
对于每个系统，确定它依赖什么。如果系统 A 没有系统 B 就无法运行，则系统 A "依赖" 系统B。
步骤 3a：映射依赖
对于每个系统，列出其依赖项。使用以下依赖启发式规则：
- 输入/输出依赖：系统 A 产生系统 B 需要的数据
- 结构依赖：系统 A 提供系统 B 接入的框架
- UI 依赖：每个游戏系统都有对应的 UI 系统，UI 系统依赖于它（但 UI 在游戏系统之后设计）
步骤 3b：按依赖顺序排序
将系统排列为层级：
- 基础层：零依赖的系统（首先设计和构建）
- 核心层：仅依赖基础层系统的系统
- 功能层：依赖核心层系统的系统
- 表现层：包裹游戏系统的 UI 和反馈系统
- 打磨层：元系统、教程、分析、无障碍
步骤 3c：检测循环依赖
检查依赖图中的循环。如果发现：
- 向用户高亮显示
- 提出解决方案（接口抽象、同时设计、通过定义两系统间的契约来打破循环）
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.
- 1mo ago First seen · 261 lines · 32 tokens per session scan A d3d20da7f092
map-systems is a skill published in the GitHub repository pixel-cellar/Claude-Code-Game-Studios (361 stars, last pushed 6mo ago), licensed MIT. It adds 32 tokens to every session and 3,069 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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