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 gongyijie85/mattpocock-skills-dsh-zh --skill domain-modeling-zhgit clone --depth 1 https://github.com/gongyijie85/mattpocock-skills-dsh-zhWrote 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/gongyijie85/mattpocock-skills-dsh-zh/domain-modeling-zh)<a href="https://agentmods.dev/skills/gongyijie85/mattpocock-skills-dsh-zh/domain-modeling-zh"><img src="https://agentmods.dev/badge/skills/gongyijie85/mattpocock-skills-dsh-zh/domain-modeling-zh/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/gongyijie85/mattpocock-skills-dsh-zh/domain-modeling-zh"><img src="https://agentmods.dev/badge/skills/gongyijie85/mattpocock-skills-dsh-zh/domain-modeling-zh.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 | $0.00043 | $0.00907 |
| Opus 5.5 | $0.00017 | $0.00363 |
| Sonnet 5.5 | $0.00009 | $0.00181 |
| Haiku 4.5 | $0.00004 | $0.00091 |
Grade A, and why
domain-modeling-zh 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.
What it actually says
Domain Modeling
在设计过程中主动构建并打磨项目的 domain model。这是一种主动的纪律 — 质疑术语、虚构 edge-case(边界情况)场景,并在术语和决策成形的瞬间把它们写下来。(仅仅阅读 CONTEXT.md 获取词汇不是本 skill 的职责 — 那是任何 skill 都能做到的一行习惯。本 skill 适用于你在改变模型,而不只是消费它的时候。)
文件结构
大多数仓库只有一个 context:
/
├── CONTEXT.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
如果根目录存在 CONTEXT-MAP.md,说明仓库有多个 contexts。该地图指向每个 context 所在的位置:
/
├── CONTEXT-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── CONTEXT.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── CONTEXT.md
│ └── docs/adr/
惰性创建文件 — 只有当你确实有东西要写时才创建。如果不存在 CONTEXT.md,在第一个术语被确定时创建它。如果不存在 docs/adr/,在需要第一个 ADR 时创建它。
会话期间
对照 glossary 提出质疑
当用户使用的术语与 CONTEXT.md 中现有的语言冲突时,立即指出来。"你的 glossary 把 'cancellation' 定义为 X,但你似乎指的是 Y — 到底是哪个?"
打磨模糊的语言
当用户使用含糊或一词多义的术语时,提出一个精确的规范术语。"你在说 'account' — 你指的是 Customer 还是 User?那是两个不同的东西。"
讨论具体的场景
当讨论 domain 关系时,用具体的场景对它们做压力测试。虚构一些探针式 edge cases 的场景,迫使用户对概念之间的边界保持精确。
与代码交叉对照
当用户陈述某样东西如何运作时,检查代码是否一致。如果发现矛盾,把它摆到台面上:"你的代码取消整个 Orders,但你刚才说部分取消是可能的 — 哪个是对的?"
即时更新 CONTEXT.md
当一个术语被确定时,就地更新 CONTEXT.md。不要批量积攒 — 随时发生随时记录。使用 CONTEXT-FORMAT.md 中的格式。
CONTEXT.md 应该完全不含 implementation 细节。不要把 CONTEXT.md 当作 spec、草稿本或 implementation 决策的仓库。它是 glossary,仅此而已。
谨慎地提议 ADR
只有当以下三件事都成立时,才提议创建 ADR:
- 难以逆转(Hard to reverse) — 日后改变主意的成本是实质性的
- 脱离上下文会令人费解(Surprising without context) — 未来的读者会想 "why did they do it this way?(他们为什么这样做?)"
- 真实权衡的结果(The result of a real trade-off) — 存在真正的备选方案,而你出于具体原因选择了其中一个
如果三者缺一,跳过 ADR。使用 ADR-FORMAT.md 中的格式。
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 · 75 lines · 43 tokens per session scan A 309d9f28735a
domain-modeling-zh is a skill published in the GitHub repository gongyijie85/mattpocock-skills-dsh-zh (8 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 907 once invoked, about $0.0002 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 2026-09-11.
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