Data Architecture

Organization

devcodex-labs

data-architecture

数据架构专家 Owner — 当任务涉及数据模型、Schema、迁移、索引、查询、生命周期、数据质量、派生指标、分析消费者、跨环境数据或持久化状态时使用；要求把数据结构、演进和消费链设计清楚。

Overview

Publisher	devcodex-labs
Repository	`devcodex`
Skill name	`data-architecture`
Stars	433
Forks	44
Bundled files	1
License	AGPL-3.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by devcodex-labs on GitHub. Read the source before you install it.

Installation

Install the Data Architecture AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/devcodex-labs/devcodex/tree/main/content/skills/data-architecture
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/devcodex-labs/devcodex.git /tmp/devcodex
mkdir -p .claude/skills
cp -r /tmp/devcodex/content/skills/data-architecture .claude/skills/data-architecture

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Data Architecture in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Data Architecture on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Data Architecture is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Data Architecture Skill

定位

本 Skill 负责数据架构 Owner 视角。它关注数据如何建模、迁移、查询、维护质量、被谁消费，以及生命周期如何闭环。

触发条件

场景	是否触发
数据模型、Schema、migration、索引、查询、缓存、持久化状态、派生指标	必须
涉及跨环境数据补齐、导入导出、数据质量、保留策略或分析消费者	必须
修改 Profile、台账、报告字段或运行态状态结构	必须
纯静态文案或无状态计算	N/A + skipReason

核心门禁

Gate	要求	证据
`DataArchitectureGate`	数据模型、迁移、索引、生命周期、质量和消费者必须成矩阵	dataModel、schemaMigration
`DataModelBoundaryGate`	业务实体、关系、字段、约束和稳定键必须明确	dataModel
`MigrationSafetyGate`	迁移、回滚、dry-run、重复/缺失处理必须可验证	schemaMigration
`QueryIndexGate`	查询路径、索引、分页和性能边界必须说明	queryIndexPlan
`DataQualityLifecycleGate`	数据质量、保留、清理、派生消费者必须明确	dataQuality、lifecycleRetention

执行步骤

建立数据模型和消费者清单。
确定稳定业务键、唯一性、关系、生命周期和保留策略。
设计迁移路线、dry-run、回滚和缺失/重复清单。
评估查询、索引、分页、缓存和性能。
绑定数据质量、派生指标、分析消费者和验证证据。

输出字段

markdown
## DataArchitectureGate

| 字段 | 内容 |
|------|------|
| dataModel | 实体、关系、字段、约束、稳定键 |
| schemaMigration | 迁移、dry-run、回滚、缺失/重复处理 |
| queryIndexPlan | 查询路径、索引、分页、性能边界 |
| lifecycleRetention | 生命周期、保留、清理、归档 |
| dataQuality | 完整性、一致性、重复、异常数据策略 |
| analyticsConsumer | 派生指标、报表、日志、消费者影响 |
| evidenceMatrix | 判断 -> schema / migration / query / tests / samples / docs |

反模式

反模式	修正
直接使用源环境 `_id` 写目标环境	用稳定业务键或显式映射清单
只改字段不评估消费者	列 analyticsConsumer 和 derived consumer
无 dry-run 的数据迁移	补范围、预览、缺失/重复、回滚
查询无索引和分页判断	补 queryIndexPlan

与其他 Skill 的关系

dev-database：数据库 schema 变更使用专门 migration 安全策略。
api-contract-architecture：数据字段进入 public API 时必须同步契约。
quality-strategy：数据质量需要测试和回归矩阵。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

intent.json1 KB

Frequently asked questions

What does the Data Architecture AI skill do?

Why use Data Architecture on TypingMind?

Because you install it once and use it with any model. Data Architecture is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Data Architecture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/devcodex-labs/devcodex/tree/main/content/skills/data-architecture. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Data Architecture?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Data Architecture?

As many as you like. As long as a model supports skills, you can use Data Architecture with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Data Architecture AI skill free?

Yes. It is published on GitHub by devcodex-labs under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Data Architecture Skill

定位

触发条件

核心门禁

执行步骤

输出字段

反模式

与其他 Skill 的关系

Bundled files

Frequently asked questions

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