design-entity

design-entity is a skill for Claude Code from ZTE-AICloud/Co-OmniSpec. It costs 37 tokens per session (2,544 once invoked), scanned A, original, MIT.

A design step that identifies the logical parts of a feature, their responsibilities, relationships, and important data. These parts are business boundaries, such as a billing or account area.

In plain words
What is it for?
Use it after a feature has been defined to document its entities, assign each function an owner, describe collaboration, and record key data structures.
Why use it?
It helps divide a feature into understandable components and prevents unclear ownership or circular dependencies between them.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the omni-dsdd plugin — 40 skills, 16 agents, 1 hook shipped together

Good fit Use it after a feature has been defined to document its entities, assign each function an owner, describe collaboration, and record key data structures.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zte-aicloud/co-omnispec/design-entity
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.

Any agent
npx skills add ZTE-AICloud/Co-OmniSpec --skill design-entity
Clone the repo
git clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpec

Made for: Claude Code.

Or install omni-dsdd, the plugin that ships this one along with the rest of its 40 skills, 16 agents, 1 hook.

Wrote 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.

agentmods badge for design-entity

README.md
[![agentmods](https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/design-entity/github.svg)](https://agentmods.dev/skills/zte-aicloud/co-omnispec/design-entity)
Your own site
<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.

agentmods 80×15 button for design-entity

Your own site · 80×15
<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>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,544 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00037 $0.02544
Opus 5 $0.00018 $0.01272
Sonnet 5 $0.00007 $0.00509
Haiku 4.5 $0.00004 $0.00254

Measured 10d ago against content hash 57ed9d68218a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

omni-dsdd/skills/design-entity/SKILL.md · 142 lines

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 design skill 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:

  1. FEATURE_DIR/spec.md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)
  1. 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_SPECcontext.md 与 IMPL_DESIGN 已有上下文自行给出分层假设并显式记录:

  1. ${DOC_DIR}/on-demand/logic_architecture.md(按需反构,优先)
  2. ${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_SPECcontext.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):
    • context_mode = evidence_first,优先消费 on_demand.scopeon_demand.traceabilityon_demand.riskson_demand.evidence_gaps,并以 in-scope 功能为实体识别起点。

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。
  • 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。

Read the full file on GitHub · 142 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. 10d ago First seen · 142 lines · 37 tokens per session scan A 57ed9d68218a

Subscribe to this mod's changes

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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