KS
Killer-Skills

cleanddd-requirements-analysis — how to use cleanddd-requirements-analysis how to use cleanddd-requirements-analysis, cleanddd-requirements-analysis setup guide, cleanddd-requirements-analysis alternative, cleanddd-requirements-analysis vs traditional modeling, what is cleanddd-requirements-analysis, cleanddd-requirements-analysis install, cleanddd-requirements-analysis for AI agents, CleanDDD modeling with cleanddd-requirements-analysis, cleanddd-requirements-analysis best practices

v1.0.0
GitHub

About this Skill

Ideal for CleanDDD Modeling Agents requiring precise demand clarification and decomposition capabilities. cleanddd-requirements-analysis is a skill that analyzes and structures business demands for CleanDDD modeling, identifying stakeholders, business entities, and triggers

Features

Gets and confirms scope by collecting business scenarios, roles, inputs, and outputs
Identifies stakeholders and their corresponding demands
Splits demands into executable items based on create, read, update, and delete operations
Classifies business entities and records core responsibilities and constraints
Identifies trigger scenarios and records subsequent actions
Supplements key business rules and input/output information

# Core Topics

LDmoxeii LDmoxeii
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
20
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add LDmoxeii/only-danmuku/cleanddd-requirements-analysis

Agent Capability Analysis

The cleanddd-requirements-analysis MCP Server by LDmoxeii is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use cleanddd-requirements-analysis, cleanddd-requirements-analysis setup guide, cleanddd-requirements-analysis alternative.

Ideal Agent Persona

Ideal for CleanDDD Modeling Agents requiring precise demand clarification and decomposition capabilities.

Core Value

Empowers agents to perform comprehensive content analysis, producing structured demand descriptions through demand clarification, stakeholder identification, and business entity classification, utilizing CleanDDD modeling principles and techniques.

Capabilities Granted for cleanddd-requirements-analysis MCP Server

Automating demand decomposition for CleanDDD modeling
Generating structured demand descriptions for business stakeholders
Identifying and categorizing business entities for domain-driven design

! Prerequisites & Limits

  • Requires prior business requirements or change statements
  • Limited to demand analysis and description, does not perform modeling or implementation
Project
SKILL.md
2.8 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

[No tags]
SKILL.md
Readonly

CleanDDD 需求分析技能

面向 CleanDDD 建模前的需求澄清与拆解,产出的结构化需求描述(场景、干系人、业务实体归类),便于后续建模或实现。

前置输入

  • 已获得业务需求/变更说明(文档、会议纪要或对话)。
  • 未经模型化或需要对现有模型做重大调整时,先运行本技能再交给 cleanddd-modeling。

工作流(只做需求分析与结构化描述,不做建模定义)

  1. 获取与确认范围:收集业务场景、角色、输入输出、约束;缺失信息先追问。
  2. 干系人识别:列出所有参与角色(如 C 端客户、后台管理员、审计、运营等),明确每条需求面向的对象。
  3. 需求拆分:按“查看/创建/修改/关闭/异步任务”切分为可执行条目,给需求ID,并标注对应干系人。
  4. 业务实体归类:将需求条目按负责满足需求的业务实体/领域对象归类,记录核心职责与约束(不做聚合/命令/事件建模)。
  5. “当 X 时做 Y”触发场景:识别事件/状态/操作触发的后续动作,按“触发条件 → 动作/影响 → 涉及角色/实体”记录,仍停留在需求级,不进入建模。
  6. 约束与输入输出:补充关键业务规则、前置条件、依赖系统或数据;标注缺口与假设。
  7. 汇总输出并二次确认:向用户呈现表格,标注假设与待确认项。

输出格式(结构化 Markdown)

  • 干系人表:角色 | 目标/痛点 | 权限/限制 | 备注
  • 需求条目表:需求ID | 场景描述 | 干系人/对象 | 所属业务实体 | 操作类型(查看/创建/修改/关闭/异步等) | 约束/前置 | 备注/缺口
  • 业务实体视图:业务实体 | 覆盖的需求条目 | 主要职责/规则 | 关键输入/输出
  • 触发/后续动作表:触发条件(当 X 操作/事件/状态) | 后续动作/影响(就做 Y) | 相关干系人 | 受影响的业务实体 | 备注/假设
  • 业务规则与依赖(可选):规则/约束 | 相关实体 | 依赖系统/数据 | 备注
  • 假设与待确认清单:项 | 描述 | 责任人 | 截止/优先级

统一命名与放置约定

  • 表格命名与列头:统一按章节中的表头格式输出,便于下游技能解析。
  • 术语统一:本技能停留在“需求级”术语,避免提前引入聚合/命令等建模术语;与 cleanddd-modeling 的术语区分清晰。
  • 文档位置:建议将本技能输出保存为仓库内 analysis/requirements.md 或由 Agent 汇总在会话记录中,便于后续 cleanddd-modeling 引用。

产出后提醒

  • 在输出末尾附“参数汇总 + 是否执行”提示,便于后续确认或传递给下游建模技能。
  • 明确未决问题与假设,便于后续建模或实现阶段承接。

Related Skills

Looking for an alternative to cleanddd-requirements-analysis or building a Categories.community AI Agent? Explore these related open-source MCP Servers.

View All

widget-generator

Logo of f
f

widget-generator is an open-source AI agent skill for creating widget plugins that are injected into prompt feeds on prompts.chat. It supports two rendering modes: standard prompt widgets using default PromptCard styling and custom render widgets built as full React components.

149.6k
0
Design

chat-sdk

Logo of lobehub
lobehub

chat-sdk is a unified TypeScript SDK for building chat bots across multiple platforms, providing a single interface for deploying bot logic.

73.0k
0
Communication

zustand

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication

data-fetching

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication