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Agent Skill · 研究检索

scan-domain-entities(扫描域实体)

scan-domain-entities 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

scan-domain-entities 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 63,254。

总安装 318周安装 13GitHub Stars 6下载 103核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:scan-domain-entities(扫描域实体)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/scan-domain-entities
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill scan-domain-entities
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/duc01226/easyplatform --skill scan-domain-entities

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

scan-domain-entities 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于根据关键词、任务场景或来源线索进行信息搜集与整理。通过 npx skills add 命令从指定 GitHub 仓库安装使用。

建议确认权限范围和维护状态,避免触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/scan-domain-entities

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/duc01226/easyplatform --skill scan-domain-enti…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

scan-domain-entities 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill scan-domain-entities。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

scan-domain-entities 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

scan-domain-entities 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

scan-domain-entities 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

scan-domain-entities 用的人多吗?

公开数据是累计安装 318 次,近一周安装 13 次,下载 103 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

scan-domain-entities 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
scan-domain-entities

扫描域实体 · 本页

3186只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Prerequisites: MUST ATTENTION READ before executing:

Scan & Update Reference Doc — When updating reference docs: (1) Read existing doc first. (2) Scan codebase for current state (grep/glob). (3) Diff findings vs doc content. (4) Update ONLY sections where code diverged from doc. (5) Preserve manual annotations. (6) Update metadata (date, counts). NEVER rewrite entire doc — surgical updates only.
Output Quality — Reference docs are injected into AI context. Apply 10 rules: (1) No inventories/counts — AI can grep. (2) No directory trees — AI can glob. (3) No TOCs. (4) Rules > descriptions — "MUST ATTENTION use X" not "X allows you to...". (5) 1 example per pattern. (6) Tables > prose. (7) BAD/GOOD pairs: 2-3 lines each. (8) Primacy-recency anchoring — critical rules in first AND last 5 lines. (9) No checkbox checklists — bullets force reading. (10) Density target: >=8 MUST ATTENTION/NEVER/ALWAYS per 100 lines.

Quick Summary

Goal: Scan project codebase and populate docs/project-reference/domain-entities-reference.md with domain entities, data models, DTOs, aggregate boundaries, cross-service entity sync maps, and Mermaid ER diagrams. (content auto-injected by hook — check for [Injected:...] header before reading)

Workflow:

  1. Read — Load current target doc, detect init vs sync mode
  2. Scan — Discover entities, models, DTOs, relationships via parallel sub-agents
  3. Report — Write findings to external report file
  4. Generate — Build/update reference doc from report
  5. Verify — Validate entity references point to real files

Key Rules:

  • Generic — works with any framework (.NET, Node.js, Java, Python, game engines, etc.)
  • Detect framework first, then scan for framework-specific entity patterns
  • For microservices: unify cross-service entities (identify owner vs consumer services)
  • Every entity reference must come from actual project files with file:line references
  • Detail level: summary + key properties (IDs, FKs, status fields, relationships) — NOT full property listing

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Scan Domain Entities

Phase 0: Read & Assess

  1. Read docs/project-reference/domain-entities-reference.md
  2. Detect mode: init (placeholder) or sync (populated)
  3. If sync: extract existing sections and note what's already documented

Phase 1: Plan Scan Strategy

Detect Project Type & Framework

Scan for project type indicators in this priority order:

  1. Check docs/project-config.json — Use modules[] for service paths, project.languages for tech stack
  2. Filesystem detection fallback:
IndicatorFrameworkEntity Patterns to Search
.csproj.NETEntity, AggregateRoot, ValueObject, IEntity, BaseEntity, project entity base
package.json + ORMNode.jsMongoose Schema, TypeORM @Entity, Prisma model, Sequelize define
pom.xml / build.gradleJava/KotlinJPA @Entity, Spring Data, Hibernate, @Table
requirements.txt / pyproject.tomlPythonDjango models.Model, SQLAlchemy, Pydantic BaseModel
*.protoProtobufmessage definitions (cross-service contracts)
Unity project filesUnityScriptableObject, MonoBehaviour data classes
Unreal project filesUnrealUObject, USTRUCT, UCLASS data types
  1. Generic fallback (any project): scan for class.*Entity, class.*Model, class.*Dto, interface.*Repository, schema, @table, collection

Detect Architecture Type

  • Microservices: Multiple service directories with separate domain layers → enable cross-service entity sync analysis
  • Monolith: Single domain layer → skip cross-service analysis
  • Modular monolith: Single deployment but bounded contexts → analyze module boundaries

Use docs/project-config.json modules[] to identify service boundaries. If unavailable, detect from directory structure.

Phase 2: Execute Scan (Parallel Sub-Agents)

Launch 3-4 Explore agents in parallel:

Agent 1: Domain Entities & Aggregates

  • Grep for entity base class inheritance (framework-specific patterns from Phase 1)
  • Find aggregate root classes
  • Find value objects
  • Find enum types used as entity properties
  • For each entity: note key properties (ID, foreign keys, status/state fields, timestamps)
  • Note file paths with line numbers

Agent 2: DTOs, ViewModels & Application Layer Models

  • Grep for DTO classes (*Dto, *DTO, *ViewModel, *Response, *Request)
  • Find command/query objects that carry entity data
  • Identify DTO-to-Entity mapping patterns (who owns mapping, method names)
  • Note which DTOs map to which entities

Agent 3: Database Schemas & Persistence

  • Find database collection/table definitions
  • Find migration files that create/alter entity tables
  • Find index definitions on entities
  • Find seed data files
  • Identify database technology per service (MongoDB, SQL Server, PostgreSQL, etc.)

Agent 4: Cross-Service Entity Sync (microservices only)

  • Grep for integration event classes (*IntegrationEvent, *Event, *Message)
  • Find message bus consumers that sync entity data across services
  • Identify shared contracts/DTOs between services
  • Map: which entity originates in which service, which services consume it
  • Find event handler classes that create/update projected entities

Write all findings to: plans/reports/scan-domain-entities-{YYMMDD}-{HHMM}-report.md

Phase 3: Analyze & Generate

Read the report. Build these sections:

Target Sections

SectionContent
Entity CatalogTable per service/module: entity name, key properties (IDs, FKs, status), base class, file path
Entity RelationshipsMermaid ER diagram per service showing entity relationships (1:N, N:M, 1:1)
Cross-Service Entity MapTable: entity name, owner service, consumer services, sync mechanism (event name), sync direction
DTO MappingTable: DTO class → Entity class, mapping approach (manual/auto), file path
Aggregate BoundariesWhich entities form aggregates, aggregate root identification
Naming ConventionsDetected naming patterns (suffixes, prefixes, namespace conventions)

Entity Catalog Format

For each service/module, produce a table:

### {ServiceName} Entities

| Entity   | Key Properties                | Base Class | Relationships          | File                   |
| -------- | ----------------------------- | ---------- | ---------------------- | ---------------------- |
| Employee | Id, CompanyId, UserId, Status | EntityBase | 1:N Goals, 1:N Reviews | `path/Employee.cs:L15` |

Detail level: Summary + key properties only. Include: IDs, foreign keys, status/state fields, important business fields. Do NOT list every property.

Cross-Service Entity Map Format (microservices)

When the same entity concept appears in multiple services:

| Unified Entity | Owner Service | Consumer Services  | Sync Event           | Direction         |
| -------------- | ------------- | ------------------ | -------------------- | ----------------- |
| Employee       | ServiceA      | ServiceB, Accounts | EmployeeCreatedEvent | Owner → Consumers |

Mermaid ER Diagram Guidelines

  • One diagram per service/bounded context (keep diagrams readable)
  • One cross-service diagram showing entity sync flows
  • Use Mermaid erDiagram syntax
  • Show only key relationships, not every FK
erDiagram
    Employee ||--o{ Goal : "has"
    Employee ||--o{ Review : "receives"
    Goal ||--o{ CheckIn : "tracks"

Content Rules

  • Show actual entity class declarations (3-5 lines) with file:line references
  • Include count of entities per service
  • Group by service/module, not by entity type
  • For microservices: highlight cross-service boundaries clearly

Phase 4: Write & Verify

  1. Write updated doc with <!-- Last scanned: YYYY-MM-DD --> at top
  2. Verify: 5+ entity file paths exist (Glob check)
  3. Verify: class names in catalog match actual class definitions (Grep check)
  4. Report: sections updated, entities discovered, coverage gaps

Closing Reminders

  • IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • IMPORTANT MUST ATTENTION read existing doc first, scan codebase, diff, surgical update only. Never rewrite entire doc.
  • IMPORTANT MUST ATTENTION follow output quality rules: no counts/trees/TOCs, rules > descriptions, 1 example per pattern, primacy-recency anchoring.

平台分布

Codex

38.75%
按下载量换算40

Claude

30.04%
按下载量换算31

Cursor

18.42%
按下载量换算19

Gemini CLI

9.18%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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