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Write Architecture Docs

OrganizationPopular
prisma
write-architecture-docs

Write or rewrite architecture subsystem docs, ADRs, and reference material for the engineering team. Use when creating, updating, or reviewing docs under docs/architecture docs/, or when the user asks you to write documentation that describes the system's design.

Overview

Publisherprisma
Repositoryorm
Skill namewrite-architecture-docs
Stars
47.6K
Forks
2.5K
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Write Architecture Docs 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.
  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/prisma/orm.git /tmp/orm
mkdir -p .claude/skills
cp -r /tmp/orm/skills-contrib/write-architecture-docs .claude/skills/write-architecture-docs
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Write Architecture Docs 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 Write Architecture Docs 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 Write Architecture Docs 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.

Writing Architecture Documentation

Architecture docs in this repo serve two audiences: team members working on the system (need precise reference material) and team members seeking context (need an accessible narrative). The doc must work for both without requiring prior project context.

Before writing

  1. Read at least two sibling docs in the same directory (e.g., other subsystem docs under docs/architecture docs/subsystems/). Calibrate your voice, structure, and level of detail to match them.
  2. Read the ADRs you'll reference. Don't just link to them — understand them well enough to summarize the key idea inline, so the reader doesn't have to follow the link to understand the doc.

Voice and framing

Write about the system, not the project. These docs describe the intended system as far as we know it. They are not project retrospectives, sprint summaries, or PoC reports.

  • State facts: "The execution pipeline generalizes across families" — not "The PoC validated that the execution pipeline generalizes"
  • No transient project references: avoid "workstream", "PoC", "sprint", "milestone", "being validated", "current effort"
  • No product comparisons: don't reference other products or prior versions. Describe what the system is, not what it improves upon.
  • Non-goals are architectural boundaries, not "not yet done" items. No (current) qualifiers.

Write for a developer without prior context. Imagine someone joining the team and reading this doc as their first exposure to this part of the system.

  • Explain why before what. Before introducing a concept like model ownership, explain the problem it solves: "In SQL, related data lives in separate tables and is joined at query time. In MongoDB, the idiomatic pattern is to store related data inside the parent document."
  • Let ideas breathe. Don't compress three concepts into one sentence. If a sentence requires the reader to already understand three things to parse it, break it apart.
  • Use concrete examples — code snippets, JSON fragments, "a developer writing X gets Y under the hood." Abstract descriptions are hard to pin understanding to.

Structure

Lead with a grounding example. Put a concrete, complete code snippet, JSON example, or diagram near the top of the document — right after the overview — so the reader has a visual reference to pin their understanding to as they read. Abstract explanations are much easier to follow when the reader can refer back to something tangible. Annotate the example with brief callouts that preview the key concepts ("notice that storage: {} means this model is embedded"). The detailed sections that follow can then elaborate on what the reader has already seen.

Articulate design principles early. If the subsystem's design is shaped by a set of principles or invariants, state them explicitly after the grounding example and before the detailed sections. This gives the reader the reasoning framework they need to understand why specific decisions were made. Each principle should be one or two sentences of plain language, not jargon. Later sections can reference the principles by number (e.g., "see design principle #5") to connect specific decisions back to their rationale.

Narrative flow. Guide the reader from one concept to the next. Don't list a set of problems and then separately list a set of solutions — pair each problem with its solution so the reader builds understanding incrementally.

Overview section. Open with plain language explaining what this part of the system is and why it exists. The first sentence should be immediately understandable by any engineer. Save technical details for later sections.

Good: "Prisma 8 supports multiple database families. SQL was the first; MongoDB is the second." Bad: "MongoDB is a database family in Prisma 8. The contract, ORM, execution pipeline, and plugin framework all generalize across fundamentally different data models — the same ContractBase domain structure, the same Collection chaining API, and the same plugin lifecycle work for both SQL and MongoDB."

Inline summaries with ADR links. When referencing an ADR, summarize the key idea in the text and link the ADR for depth. The doc should be understandable without following any links. The example below shows the link as it must appear in the subsystem doc you are writing, so its path is relative to that doc's location under docs/architecture docs/subsystems/.

Good: "An owned model declares owner: \"User\" — a domain fact about aggregate membership. Its data lives within the owner's storage. See ADR 177." Bad: "See ADR 177 for how embedding works."

References section. Organize by durability:

  1. Architecture decisions (ADRs) — first
  2. Durable reference material — second
  3. Historical context (planning docs) — last, labeled as such

Anti-patterns

  • Compressed summaries. A paragraph that reads like a bulleted list crammed into prose. If you're listing things, use a list.
  • Jargon without introduction. Don't use terms like "aggregate root", "discriminator narrowing", or "STI" without explaining what they mean in context.
  • ADR-as-explanation. Pointing to an ADR instead of explaining the concept. ADR links are for depth; the doc must stand alone.
  • Project-process narrative. "We built X, then discovered Y, which led to Z." Describe what the system is, not how we arrived at it.
  • Terse overview + detailed body. The overview should be the most accessible part of the doc, not the most compressed.

Quality check

Before finishing, re-read the doc as a developer who has never seen it before. For each paragraph, ask:

  • Can I understand this without context from outside this doc?
  • Does it explain why before what?
  • Would a concrete example help here?
  • Am I stating a fact about the system, or narrating a project?

Frequently asked questions

What does the Write Architecture Docs AI skill do?

Write or rewrite architecture subsystem docs, ADRs, and reference material for the engineering team. Use when creating, updating, or reviewing docs under docs/architecture docs/, or when the user asks you to write documentation that describes the system's design.

Why use Write Architecture Docs on TypingMind?

Because you install it once and use it with any model. Write Architecture Docs 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 Write Architecture Docs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prisma/orm/tree/main/skills-contrib/write-architecture-docs. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Write Architecture Docs?

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 Write Architecture Docs?

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

Is the Write Architecture Docs AI skill free?

Yes. It is published on GitHub by prisma under the Apache-2.0 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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