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Architect

Organization
nagi-studio
architect

技术选型(tech stack):需求清楚之后,比较两三套方案并推荐一套。用于新项目选框架、数据库、托管和部署方式,或用户问「用什么技术做」「怎么部署」、which stack、how to host。

Overview

Publishernagi-studio
Repositoryskills
Skill namearchitect
Stars
277
Forks
3
Bundled files
1
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.

  • 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 nagi-studio on GitHub. Read the source before you install it.

Installation

Install the Architect 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/nagi-studio/skills/tree/main/skills/pondering/architect
  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/nagi-studio/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/pondering/architect .claude/skills/architect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Architect 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 Architect 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 Architect 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.

先读需求:docs/decisions-*.md,以及本次对话里已经定下的结论。从中取出下列约束;缺的、且会改变选型的,问一轮(每个问题写 ❓ Q1|标题、问题、➡️ 建议)。

  • 使用地区:中国大陆、海外,还是都有
  • 平台和规模:网页 / 手机 / 桌面;多少人用,会不会涨
  • 数据:要不要登录、同步、多人协作;放本地还是云端
  • 用户能亲手维护什么:按经历问(部署过网站?管过数据库?用过环境变量?),不问自评
  • 预算和硬约束:持续成本、指定服务、网络、合规

措辞跟着用户的水平走,从他们的回答里随时调整:对新手,每个术语第一次出现时附一句白话。

价格、免费额度、地区可用性、官方支持情况,现查官方页面并附链接;记忆里的数字常常过时。

需求里有成熟的库或现成服务能解决的部分,方案里直接用,不自己写。「成熟」看三点:和需求对得上、有测试、有人持续维护。也要防供应链风险:优先选有可靠背书的(知名公司、基金会或团队维护,用的人多),包名核对清楚,来路不明的小包不装。在开源自建和托管服务之间,选用户维护得了的那个。

给两到三套方案,按「成熟稳妥的技术(boring technology)」排序:第一套是用户管得过来的最简单方案。每套写:

### 方案 A:一句话名字
- 技术栈:
- 为什么适合:
- 开发难度 / 维护成本:
- 目标地区能否顺利使用:
- 你得自己管的东西:密钥放哪、权限规则、要打补丁的服务器;没有就写「无」
- 主要风险:

最后写「推荐:方案 X」和起决定作用的那条理由,再列仍会改变推荐的待定问题(没有就写「无」)。

用户选定后,把方案和理由追加进 decisions 文件(没有就新建 docs/decisions-<英文主题>.md;不能写文件就输出可复制的 Markdown)。

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 Architect AI skill do?

技术选型(tech stack):需求清楚之后,比较两三套方案并推荐一套。用于新项目选框架、数据库、托管和部署方式,或用户问「用什么技术做」「怎么部署」、which stack、how to host。

Why use Architect on TypingMind?

Because you install it once and use it with any model. Architect 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 Architect in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nagi-studio/skills/tree/main/skills/pondering/architect. 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 Architect?

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 Architect?

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

Is the Architect AI skill free?

Yes. It is published on GitHub by nagi-studio 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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