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Use when a learner asks for help with MATLAB homework, labs, projects, graded assignments, take-home exams, quizzes, or any programming task where academic…
Use this skill for the architecture phases of an MBSE workflow in MATLAB, when writing idempotent buildXxx.m scripts that produce a three-layer RFLPV architecture (Functional, Logical, Physical) with interface dictionaries, stereotype profiles, allocation sets, and requirements
$ npx -y skills add matlab/agent-skills-playground --skill mbse-architecture --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/mbse-architectureContext preview
The summary Claude sees to decide when to auto-load this skill.
Use this skill for the architecture phases of an MBSE workflow in MATLAB, when writing idempotent buildXxx.m scripts that produce a three-layer RFLPV architecture (Functional, Logical, Physical) with interface dictionaries, stereotype profiles, allocation sets, and requirements
name: mbse-architecture description: Use this skill for the architecture phases of an MBSE workflow in MATLAB, when writing idempotent buildXxx.m scripts that produce a three-layer RFLPV architecture (Functional, Logical, Physical) with interface dictionaries, stereotype profiles, allocation sets, and requirements Implement links. Trigger for defining stereotype properties, functional-to-logical / logical-to-physical allocation, mapping requirements to components via slreq Implement links, or running quantitative roll-up analysis on the architecture. Do NOT trigger for ad-hoc structural edits to an already-built System Composer model (adding one component, rewiring a port) — use `building-simulink-models` with `model_edit` for that. Works alongside the `system-composer` skill for detailed SC API patterns. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"
See the `system-composer` skill for the full System Composer API reference (interfaces, ports, connections, auto-layout). This skill covers the MBSE-specific decisions and patterns layered on top, plus allocation and analysis.
For analysis details see `references/analysis.md` (prose) plus `code/myRollupAnalysis.m` and `code/runMyAnalysis.m` (templates).
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This skill produces reusable idempotent build scripts — the whole three-layer architecture, its interface dictionaries, profile, and allocation sets, built from scratch in one `buildAll()` run. That is its sweet spot.
For **one-off edits** to an already-built SC model — adding a single SubSystem to explore a variant, tweaking one port name, renaming a component — prefer SATK's `building-simulink-models` with the `model_edit` MCP tool. `model_edit` handles autolayout, undo, and error recovery automatically and is faster for interactive tweaks.
Once the MBSE model is in a state where you need to round-trip it through `buildPhysical.m` etc. again (for example because you added a stereotype property or changed an allocation), go back to this skill — the `buildXxx.m` scripts will rebuild from scratch and all of `model_edit`'s ad-hoc changes will be overwritten. That is intentional: the build scripts are the source of truth.
**Never mix the two in one script.** The two skills use different System Composer API layers (architecture-modeling vs. block-diagram). See the `system-composer` skill's "When to use this skill vs. `building-simulink-models`" section for the API-layer differences.
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The MBSE workflow uses three separate System Composer models, one per layer:
| Model | Layer | Answers | Interface style | |---|---|---|---| | `MyFunctional.slx` | F — Functions | What does the system *do*? | Abstract flows, solution-neutral | | `MyLogical.slx` | L — Logical | What *kind* of element solves it? | Typed signals, design-agnostic | | `MyPhysical.slx` | P — Physical | *How* is it built? | Concrete fields, physical units |
Each model has its own interface dictionary at the appropriate abstraction level. All three dictionaries are independent — no model script depends on another being open.
**Build order: Functional first, Logical second, Physical third.**
These three models are *structural* views. For a *behavioral* companion (message sequences across components for a specific scenario), attach a System Composer Interaction to the Logical model — see [`system-composer/SKILL.md#sequence-diagrams`](../system-composer/SKILL.md#sequence-diagrams). The Logical layer is the natural home because it's stable across Physical-layer variant trade studies.
The Logical layer is the key distinction from classic RFLP. Logical components are design-agnostic solution principles (e.g., `SensingUnit`, `ControlUnit`, `ActuationUnit`) — they commit to *what kind* of element is needed without specifying vendor, geometry, or implementation. Physical components are the actual realization.
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What the system *does* — logical functions and the abstract information flows between them. Creates and owns the functional interface dictionary.
See [`code/buildMyFunctional.m`](code/buildMyFunctional.m) for the full parameterized function:
buildMyFunctional(modelName, dictFile, archDir)
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What kind of element solves each function — solution principles without physical commitment. Creates and owns the logical interface dictionary.
See [`code/buildMyLogical.m`](code/buildMyLogical.m) for the full parameterized function:
buildMyLogical(modelName, dictFile, archDir)
**Naming guidance for logical components:** Use nouns that describe the *role* of the solution element, not the specific hardware. Good: `SensingUnit`, `ControlUnit`, `ActuationUnit`, `PowerConverter`. Avoid hardware brand names or part numbers — those belong in the Physical layer.
**Interface guidance:** Logical interfaces sit between functional (abstract flows) and physical (hardware-spec signals). Include typed fields with semantic meaning but without datasheet-level specifics — no voltage ranges, baud rates, or tolerance values.
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What the system *implements* — hardware/software components, physical interfaces, and stereotype properties. Creates and owns the physical interface dictionary.
See [`code/buildMyModel.m`](code/buildMyModel.m) for the full parameterized function:
buildMyModel(modelName, dictFile, archDir)
**Key gotchas:**
A sandbox for prototyping and demonstrating Agent Skills for MATLAB and Simulink work. Skills here are experimental. They may be incomplete, change without notice, or migrate to an official toolkit over time.
Repo: matlab/agent-skills-playground
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