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Building Architecture Models

OrganizationPopular
matlab
building-architecture-models

Common steps for building multi-layer system architecture models using System Composer. Use when implementing architecture models or when interacting with interface dictionaries, allocation sets, stereotypes, and requirements for architecture components.

Overview

Publishermatlab
Repositorysimulink-agentic-toolkit
Skill namebuilding-architecture-models
Stars
1.2K
Forks
112
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Building Architecture Models 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/matlab/simulink-agentic-toolkit/tree/main/skills-catalog/model-based-system-engineering/building-architecture-models
  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/matlab/simulink-agentic-toolkit.git /tmp/simulink-agentic-toolkit
mkdir -p .claude/skills
cp -r /tmp/simulink-agentic-toolkit/skills-catalog/model-based-system-engineering/building-architecture-models .claude/skills/building-architecture-models
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Building Architecture Models 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 Building Architecture Models 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 Building Architecture Models 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.

Building Architecture Models

Create and refine System Composer architecture models — from greenfield F/L/P designs to targeted additions (stereotypes, views, allocation sets, requirements tracing).

When to Use

  • Designing a system architecture (full F/L/P or single-layer)
  • Adding interface dictionaries, stereotypes, views, or roll-up analysis to existing SC models
  • Creating allocation sets between architecture layers
  • Linking requirements to architecture components (Implement links)
  • Refining existing System Composer models with methodology guidance

When NOT to Use

  • Building or editing a Simulink model (block-level work) → use building-simulink-models
  • One-off structural edits to an existing SC model (add a component, rewire a port) → use building-simulink-models with model_edit
  • User doesn't have a clear decomposition or requirements yet → suggest specifying-mbd-algorithms to produce a spec first, then return here to build
  • Creating activity/sequence behavior diagrams → These are supported features of System Composer, but are not covered in this skill. Do not suggest using Stateflow as an alternative.

Mental Model

  1. F/L/P = 3 separate Architecture models. There are no special model types (systemcomposer.createFunctionalModel does not exist). Layers are a convention — three independent .slx models connected by allocation sets.

  2. Layer conventions:

    • Functional — verb phrases (SenseState, ComputeControl), abstract interfaces, no units
    • Logical — solution-role nouns (SensingUnit, ControlUnit), typed signals, design-agnostic
    • Physical — concrete units (IMU_SensorModule, FlightComputer), physical units, implementation-level
  3. Allocation links layers. Allocation sets map elements across models (F→L, L→P). Rebuilding a model invalidates allocation links because SIDs change — always re-run allocation after a model rebuild.

  4. Interface dictionaries are per-layer. Each layer has its own .sldd with interfaces at the appropriate abstraction. The dictionary must be linked to the model (linkDictionary) before setInterface works — without it, ports silently stay untyped.

  5. Stereotypes follow a strict lifecycle. Create profile → save → apply to model → apply stereotype to components → set properties. Fully-qualified paths required: Profile.Stereotype.Property.

Guardrails

Always:

  • Get user review and approval before moving to the next phase
  • Rebuilding a model invalidates allocation links (SIDs change) — re-run allocation after any model rebuild
  • Run model_check after building each model to detect unconnected ports
  • Save models before creating allocation sets that reference them

Ask First:

  • Deviating from the top-down F→L→P build order (when doing a greenfield design)
  • Adding operating modes or layers not discussed with the user

Never:

  • Delete or overwrite a model file without user confirmation
  • Skip model_check verification after building a layer
  • Use systemcomposer.createAllocationSet — correct namespace is systemcomposer.allocation.createAllocationSet

Task Routing

IntentReference
Build a full system architecture from scratch (greenfield)references/flp-reference-workflow.md — tailor to user's scope and existing artifacts
Add interface dictionaries, stereotypes, views, or analysisreferences/system-composer-api.md
Create allocation sets between layersreferences/system-composer-api.md § Allocation Sets
Link requirements to architecture componentsreferences/requirements-traceability-api.md
Set up project for architecture workreferences/matlab-project.md + managing-simulink-projects

Prerequisites

  • The user has an active Simulink project (or assist in creating one via managing-simulink-projects)
  • Simulink, System Composer, and Requirements Toolbox are licensed

The helper scripts/resolveComponent.m is in the skill's scripts/ directory. Use evaluate_matlab_code with project_path set to the skill's scripts/ folder so MATLAB can find it. Never use addpath.

Verification

Run after building each model:

  • model_check with checks="unconnected_ports" to detect unwired ports
  • Update diagram (set_param(modelName, "SimulationCommand", "update")) to catch interface type issues

Tools Used

  • model_edit — structural modeling (components, ports, connections, layout)
  • model_check — post-build verification (unconnected ports)
  • evaluate_matlab_code — SC-specific APIs (interface dictionaries, stereotypes, allocation, views, analysis, requirements linking)
  • scripts/resolveComponent.m — helper to resolve nested sub-components by path

Copyright 2026 The MathWorks, Inc.


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 Building Architecture Models AI skill do?

Common steps for building multi-layer system architecture models using System Composer. Use when implementing architecture models or when interacting with interface dictionaries, allocation sets, stereotypes, and requirements for architecture components.

Why use Building Architecture Models on TypingMind?

Because you install it once and use it with any model. Building Architecture Models 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 Building Architecture Models in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/matlab/simulink-agentic-toolkit/tree/main/skills-catalog/model-based-system-engineering/building-architecture-models. 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 Building Architecture Models?

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 Building Architecture Models?

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

Is the Building Architecture Models AI skill free?

It is published on GitHub by matlab. Check the repository for licensing terms. 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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