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dynamodb-access-patternsDynamodb 访问模式

Agent Skill

dynamodb-access-patterns 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。

总安装

528

周安装

22

GitHub Stars

公开资料未说明

下载量

176
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:dynamodb-access-patterns(Dynamodb 访问模式)
来源仓库:https://github.com/juancarestre/dynamodb-skills
仓库路径:skills/dynamodb-access-patterns
安装命令:
npx skills add https://github.com/juancarestre/dynamodb-skills --skill dynamodb-access-patterns
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/juancarestre/dynamodb-skills --skill dynamodb-access-patterns

简介

DynamoDB 访问模式提取工具引导交互式对话以系统化梳理数据访问需求。

  • 适用于单表设计初期,帮助定义实体关系与查询路径,输出结构化文档。
  • 语言无关且项目无关,可适配任意技术栈的 DynamoDB 建模流程。
  • 需用户提供业务上下文,避免生成无法落地的抽象模型或遗漏关键约束。
  • dynamodb-access-patterns 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

DynamoDB Access Patterns

This skill guides an interactive conversation to extract, formalize, and persist all access patterns for a DynamoDB single-table design. It is language-agnostic and project-agnostic -- it works for any application regardless of tech stack.

When to Use

  • The user wants to design a new DynamoDB table from scratch
  • The user wants to add new entities to an existing DynamoDB table
  • The user says things like "I need to store X and query by Y"
  • The user wants to document their access patterns before implementation
  • The user has an existing relational schema they want to migrate to DynamoDB

Pipeline Position

  [1. Access Patterns]  -->  2. Table Design  -->  3. Query Interfaces
       (this skill)        (dynamodb-table-     (dynamodb-query-
                            design)              interfaces)

This skill produces a .md file that is consumed by dynamodb-table-design.


Interactive Workflow

Step 1: Understand the Domain

Ask the user to describe their application at a high level. You need to understand:

  1. What does the application do? (e-commerce, social network, game, SaaS, etc.)
  2. Who are the actors? (users, admins, systems, etc.)
  3. What are the main entities? (the "nouns" of the system)

Ask open-ended questions. Don't assume -- let the user describe their domain.

Example opening:

Before designing the DynamoDB table, I need to understand your domain.

1. What does your application do in one sentence?
2. What are the main entities (things you need to store)?
3. Who or what interacts with these entities?

Step 2: Catalog All Entities

For each entity the user mentions, gather:

FieldDescriptionExample
NameSingular name, PascalCaseOrder
DescriptionWhat it represents"A purchase made by a customer"
AttributesAll fields with typesorderId: string, total: number, status: string, createdAt: datetime
RelationshipsHow it relates to other entities"Belongs to a User. Contains many OrderItems."
CardinalityExpected volume"~100 orders per user, ~10M total"
LifecycleDoes it expire? Get updated? Deleted?"Updated when status changes. Archived after 1 year."

Ask the user about EACH entity systematically. Don't skip attributes -- they affect key design later.

IMPORTANT: Also identify counter/aggregate entities that the user might not think of as entities:

  • "Do you need to track counts? (e.g., number of orders per user)"
  • "Do you need running totals or balances?"
  • "Do you need any metadata records?"

Step 3: Elicit Access Patterns

This is the most critical step. For EACH entity, ask:

For [Entity], how will your application access this data?
Think about every screen, API endpoint, or background job that reads or writes this entity.

For each access pattern, capture these fields:

FieldDescription
IDSequential number (AP-001, AP-002,...)
EntityWhich entity or entities are involved
OperationRead / Write / Update / Delete
DescriptionPlain English description
Input ParametersWhat the caller provides
Result TypeSingle item, Collection, or Count
Sort RequiredNone, Ascending, Descending -- and by what field
FiltersAny conditions beyond the lookup key
PaginationYes/No -- is the result set potentially large?
FrequencyHot (>100/s), Warm (1-100/s), Cold (<1/s)
ConsistencyEventual (default) or Strong
Multi-EntityDoes this pattern need data from multiple entity types in one call?

Probing questions to uncover hidden patterns:

  • "How do you list these? All at once, paginated, or filtered?"
  • "Do you ever need to sort by anything other than creation time?"
  • "Do you need to look this up from the 'other side'?" (e.g., find user by email, not just by userId)
  • "Are there any leaderboards, rankings, or sorted lists?"
  • "Do you need to check existence before creating?"
  • "Are there any batch operations? (create 10 items at once)"
  • "Do any items have a TTL or expiration?"
  • "Do you need to fetch a parent AND its children in one call?"

Step 4: Identify Item Collection Opportunities

Review all access patterns and look for cases where multiple entity types are fetched together. These are the most valuable patterns in single-table design.

Ask the user:

Looking at your access patterns, I see some opportunities to fetch related data in a single query:

- [AP-003] and [AP-007] both need User + Orders data
- [AP-012] needs Product + Reviews together

Do these always get fetched together, or only sometimes?
Are there screens/endpoints where you need BOTH in one call?

Mark these patterns explicitly as item collection candidates.

Step 5: Identify Write Patterns and Transactions

For every write operation, determine:

  1. How many items are written per operation? (single item vs. transaction)
  2. Must they succeed or fail together? (transaction requirement)
  3. Are there conditional writes? (don't overwrite if exists, ensure parent exists, etc.)
  4. Do writes affect counters? (incrementing a count alongside creating an item)

Example questions:

When you create an Order:
- Do you also need to update the user's order count?
- Do you need to add it to a global "recent orders" list?
- Should it fail if the user doesn't exist?

Step 6: Validate Completeness

Before persisting, do a final review with the user:

Here's a summary of what I've captured:

Entities: [list]
Access Patterns: [count] total
  - Reads: [count]
  - Writes: [count]
  - Multi-entity: [count]

Missing anything? Common things people forget:
- Admin/backoffice access patterns
- Search/filtering patterns
- Reporting or analytics queries (these may go to a different system)
- Migration or bulk import patterns
- Audit trail / history patterns

Output Format

Persist the output as a markdown file. The user chooses the path, but suggest docs/dynamodb/access-patterns.md or a similar location in their project.

Read reference/output-template.md for the exact file structure to use.


Rules for the Agent

  1. Never skip the interactive conversation. Don't generate access patterns from assumptions. Always ask.
  2. Be thorough. It's better to capture 5 patterns you don't use than miss 1 you need.
  3. Challenge the user. If they say "I just need basic CRUD", push back with specific questions about sorting, filtering, pagination, and multi-entity reads.
  4. Stay language-agnostic. Use generic types: string, number, boolean, datetime, list, map. Don't use TypeScript, Python, or Java-specific types.
  5. Don't design keys yet. This skill is about WHAT data you need, not HOW to store it. Key design happens in the next skill (dynamodb-table-design).
  6. Persist the file. Always write the output to a .md file. This file is the input for the next step.
  7. Use the question tool. When you need to clarify between options, use the interactive question tool to give the user clear choices.
  8. Number everything. Access patterns must have stable IDs (AP-001, AP-002,...) because the next skill references them.
  9. Mark multi-entity patterns explicitly. These are the most important patterns for single-table design.
  10. Include write patterns. Writes determine transactions and item duplication strategy. They're as important as reads.

Next Step

Once the access patterns file is complete, tell the user:

Access patterns are documented at [file path].

The next step is to design the DynamoDB table structure -- partition keys,
sort keys, GSIs, and map each access pattern to a concrete DynamoDB operation.

To continue, use the `dynamodb-table-design` skill with this file as input.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.62%
按下载量换算66

Claude

28.79%
按下载量换算51

Cursor

18.74%
按下载量换算33

Gemini CLI

9.02%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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