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Mini Program Architecture Skill

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NocodeMrLi
mini-program-architecture-skill

Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.

Overview

PublisherNocodeMrLi
Repositorymini-program-engineering-skill-suite
Skill namemini-program-architecture-skill
Stars
91
Forks
7
Bundled files
4
LicenseMIT
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NocodeMrLi on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NocodeMrLi/mini-program-engineering-skill-suite/tree/main/skills/mini-program-architecture-skill
  4. 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.
2

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/NocodeMrLi/mini-program-engineering-skill-suite.git /tmp/mini-program-engineering-skill-suite
mkdir -p .claude/skills
cp -r /tmp/mini-program-engineering-skill-suite/skills/mini-program-architecture-skill .claude/skills/mini-program-architecture-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mini Program Architecture Skill 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 Mini Program Architecture Skill 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 Mini Program Architecture Skill 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.

/mini-program-architecture-skill — 小程序工程架构

把已经确认的产品语义映射为可实现、可验证、可迁移和可回滚的工程方案。架构服务于产品约束,不改变产品语义来迁就技术方案。

进入条件与边界

  • 需要一份稳定的产品规格、明确功能边界,或现有项目的只读事实图。
  • 已有项目先读取规则、当前源码与配置、Git 状态和必须保护的用户改动;优先延续已经有效的工程模式。
  • 若目标用户、主流程或关键数据规则仍有实质冲突,退回产品决策点,不用架构选择掩盖歧义。
  • 不直接实现代码,不决定未确认的按钮、奖励、付费、权限理由或业务状态。

架构流程

  1. 列出输入事实、产品不变量、质量目标、约束、未知项和不在本轮范围内的内容。
  2. 将页面职责映射为页面、组件、领域服务、平台适配层和外部依赖,明确每层所有权。
  3. 为关键事实指定唯一规范状态源,说明派生状态、生命周期、刷新时机与跨页同步。
  4. 定义数据模型、标识、版本、校验、读写边界和敏感字段;说明本地、云端或第三方的权威关系。涉及云端状态或持久化时按 云端状态、配置与写入安全合同 约束三态恢复、配置组、适配器和存储不变量。
  5. 定义 API 或云函数契约、认证与权限、错误分类、超时、重试、降级和可观察证据;外部服务明确“返回”和“业务结果有效”是不同门禁。
  6. 针对重复请求、离线恢复、多端写入和异步回调,明确缓存、并发、幂等与一致性策略;一次性写入和创建型幂等必须给出存储层约束及稳定重试结果。
  7. 若涉及存量数据或接口,写出兼容、迁移、灰度、回滚条件和失败后的恢复路径。
  8. 比较至少一个可行替代方案,记录选择理由、代价和需要重新评估的触发条件。
  9. 使用 架构工作流 自检,并按 架构决策记录模板 输出 ADR 与实施交接。

最低输出

  • 架构范围、事实、产品不变量、质量目标与未知项。
  • 页面/组件/服务/平台层边界及依赖方向。
  • 状态源、数据模型、接口、权限与失败策略。
  • 条件触发时的权威三态、配置完整性、适配器契约、作用域隔离、秘密摘要、有效结果提交和真实依赖健康合同。
  • 缓存、并发、幂等、一致性、迁移和回滚方案。
  • 外部依赖风险、可观察性和对应产品验收行为。
  • ADR:选择、替代方案、代价、验证方式与重新评估条件。

停止条件

关键产品语义未确认、当前项目存在无法保护的未知改动、核心外部能力不可核验,或数据迁移没有可接受回滚路径时,停止并报告具体缺口。不要用“实现时再说”隐藏高影响决策。

独立与套件协作

独立安装时,本 Skill 可基于给定规格完成架构设计。位于完整套件中时,遵守共享工程门禁和证据状态;只接收阶段产物、输出 ADR 和实施边界,不调用其他组件脚本。

Bundled files

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

Frequently asked questions

What does the Mini Program Architecture Skill AI skill do?

Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repo...

Why use Mini Program Architecture Skill on TypingMind?

Because you install it once and use it with any model. Mini Program Architecture Skill 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 Mini Program Architecture Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NocodeMrLi/mini-program-engineering-skill-suite/tree/main/skills/mini-program-architecture-skill. 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 Mini Program Architecture Skill?

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 Mini Program Architecture Skill?

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

Is the Mini Program Architecture Skill AI skill free?

Yes. It is published on GitHub by NocodeMrLi under the MIT 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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