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 BlueprintOS/analysis-to-delivery --skill domain-modelinggit clone --depth 1 https://github.com/BlueprintOS/analysis-to-deliveryWrote 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/blueprintos/analysis-to-delivery/domain-modeling)<a href="https://agentmods.dev/skills/blueprintos/analysis-to-delivery/domain-modeling"><img src="https://agentmods.dev/badge/skills/blueprintos/analysis-to-delivery/domain-modeling/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/blueprintos/analysis-to-delivery/domain-modeling"><img src="https://agentmods.dev/badge/skills/blueprintos/analysis-to-delivery/domain-modeling.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 | $0.00040 | $0.00715 |
| Opus 5 | $0.00020 | $0.00358 |
| Sonnet 5 | $0.00008 | $0.00143 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
domain-modeling 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 10d 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(桥接到 superpowers)
Contract
- Inputs: design spec, terminology, entities, business rules
- Outputs: domain model diagram and entity list
- Gates: user agrees canonical terms and relationships
- Required disciplines:
stage-gate - Next:
/writing-plans
本仓库不维护此 skill 的内容。完整纪律请读:
<SUPERPOWERS_SKILL_ROOT>/domain-modeling/SKILL.md
何时调
- brainstorming / design-an-interface 之后
- 需要定义实体、值对象、聚合根
衔接点
- 产出:领域模型图 + 实体清单
- 下一步:
/writing-plans - 门控:
disciplines/stage-gate第 2 层
降级方案(superpowers 未装时)
如果 <SUPERPOWERS_SKILL_ROOT>/domain-modeling/ 不存在,按以下 4 步产出领域模型:
1. 列实体
从 brainstorming 设计稿提取名词,过滤出实体(有生命周期、有 ID)与值对象(无 ID、不可变):
| 类型 | 例子 | 判别 |
|---|---|---|
| 实体 | ASN / LPN / 波次 | 有 *_ID,状态会变 |
| 值对象 | 收货地址 / 计量单位 | 无 ID,只描述属性 |
| 聚合根 | ASN(含 LPN 列表) | 一致性边界 |
2. 画 ASCII 关系图
参考 disciplines/ascii-flowchart 用 ASCII 画实体关系图,严禁 Mermaid:
[ASN] -- 1..N --> [ASN_DTL] -- 1..N --> [LPN]
| |
+-- 1..1 --> [收货地址(值对象)]
3. 字段对齐验证
每个实体字段必须与知识库核对(disciplines/no-field-guessing):
- 已有表 → 直接用现有字段(走
field-alignment-check.py) - 新增字段 → 标记
EXTEND且写扩展理由
4. 输出 + 签字
写到 docs/superpowers/specs/<topic>-domain.md,末尾 ## Sign-off 等用户白名单签字(4 句之一)。
最小纪律摘要
- 名词 ≠ 实体:不是所有名词都是实体,看 ID 与状态
- ASCII 不用 Mermaid:与全局
ascii-flowchart纪律冲突 - 字段不靠记忆:严禁自创字段名(
no-field-guessing+no-self-invent) - 聚合根边界 = 事务边界:不能跨聚合根强一致
安装提示
npx skills@latest add obra/superpowers-domain-modeling
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.
- 10d ago First seen · 79 lines · 40 tokens per session scan A 7659d5e9cc65
domain-modeling is a skill published in the GitHub repository BlueprintOS/analysis-to-delivery (26 stars, last pushed 2mo ago), licensed MIT. It adds 40 tokens to every session and 715 once invoked, about $0.0002 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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