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 ZTE-AICloud/Co-OmniSpec --skill design-entitygit clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpecWrote 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/zte-aicloud/co-omnispec/design-entity)<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/design-entity"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/design-entity/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/zte-aicloud/co-omnispec/design-entity"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/design-entity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00037 | $0.02544 |
| Opus 5 | $0.00018 | $0.01272 |
| Sonnet 5 | $0.00007 | $0.00509 |
| Haiku 4.5 | $0.00004 | $0.00254 |
Grade A, and why
design-entity 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.
How it starts
The opening of the file, as written. The whole thing — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
design-entity
使用时机
- 仅被
designskill 显式调用
逻辑实体定义
- 逻辑实体是承载业务能力与数据职责的逻辑边界,用于将功能切分到可演进、可协作、可验证的模块单元。
- 逻辑实体应明确其责任边界(In scope / Out of scope)、关键职责(职责清单与非职责项)、协作关系(同层协作与跨层调用方向)以及关键状态与属性(与需求相关、可被验证)。
- 逻辑实体以目录为载体: 以“具有明确业务含义的叶子目录”为最小粒度进行映射;不将
include/、source/等通用/基础设施类目录视为逻辑实体(除非该目录本身承载明确业务语义且在需求/场景中可追溯)。
注意事项:
- 以
FEATURE_DIR/spec.md的功能列表为依据,识别支撑功能所需的逻辑实体,并为每个功能明确:
- 主责逻辑实体: 对功能结果负责(每个功能至少 1 个主责实体)
- 协作逻辑实体: 为主责实体提供数据/能力支持(可为 0..N)
- 结合有效架构约束文档(见下「架构文档解析」),校验实体之间的调用方向是否合理,避免形成跨层反向依赖或循环依赖。
架构文档解析(与 design / design-interface 一致)
按以下顺序选用第一个存在的文件作为本次步骤的架构输入;均不存在则不阻塞,不将「缺少架构文件」视为失败,仅在产出中依赖 FEATURE_SPEC、context.md 与 IMPL_DESIGN 已有上下文自行给出分层假设并显式记录:
${DOC_DIR}/on-demand/logic_architecture.md(按需反构,优先)${DOC_DIR}/specs/logic_architecture.md(规格库)
下文所称「有效架构约束文档」指按上式解析得到的文件;若未解析到任何文件,则称「未加载架构文档」。
指令
步骤1: 明确输入与上下文
- 功能: 读取 IMPL_DESIGN 中的「功能」章节,获得业务意图对应的功能内容。
- 架构约束: 按「架构文档解析」加载有效架构约束文档;若已加载,据此明确系统分层、跨层调用方向与允许的依赖边界;若未加载,基于
FEATURE_SPEC与context.md做出合理分层假设并在 IMPL_DESIGN 中写明,仍须避免明显跨层反向依赖。 - 上下文文件: 优先读取
FEATURE_DIR/context.md中的「相关逻辑实体文档」章节,作为既有逻辑实体的主要参考来源。 - on-demand 上下文(可选优先):
- 若
context_mode = evidence_first,优先消费on_demand.scope、on_demand.traceability、on_demand.risks、on_demand.evidence_gaps,并以 in-scope 功能为实体识别起点。
- 若
步骤2: 分析逻辑实体
基于步骤1输入与上下文,按「逻辑实体定义」识别并产出本次变更涉及的全部逻辑实体条目(含INSERT/MODIFY/DELETE/REFER),作为后续步骤的范围基线。
动作类型定义:
- MODIFY: 业务意图要求调整既有逻辑实体的职责、结构或关键属性时。优先基于
FEATURE_DIR/context.md指向的既有逻辑实体文档进行修改。 - INSERT:
- 理解既有逻辑实体,无法合理承载新增职责或需要引入新的职责边界,且需要新增目录时,才增加逻辑实体。
- 不存在既有逻辑实体时,则新增当前目录的逻辑实体。
- DELETE: 仅在删除具有明确业务必要性且风险可控时允许;必须提供充分理由与影响分析(含依赖方与数据迁移/兼容策略)。
- REFER: 既有逻辑实体已充分覆盖当前业务意图,无需对实体内容作任何修改,但需建立引用关系以支持后续波及分析。
on-demand 实体消费规则(仅 evidence_first 模式):
- 先以
on_demand.scope中 in-scope 功能倒推主责/协作实体,限制实体分析范围。 - 利用
on_demand.traceability保证“需求-功能-接口-实体”链路可追溯,避免孤立实体。 - 对
on_demand.risks/on_demand.evidence_gaps,在实体边界或数据模型中显式记录假设与约束。 - 未在 in-scope 功能链路中且无证据支撑的新增实体,默认不纳入主设计范围。
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 · 142 lines · 37 tokens per session scan A 57ed9d68218a
design-entity is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (54 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 2,544 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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