specifying-mbd-algorithms

specifying-mbd-algorithms is a skill for Claude Code, Codex from matlab/simulink-agentic-toolkit. It costs 62 tokens per session (1,575 once invoked), scanned A, original, no licence file.

A guide for describing algorithms before they are built in MATLAB or model-based design tools. Model-Based Design means defining and testing a system with models before implementing it in a finished product.

In plain words
What is it for?
Use it to specify controllers, signal-processing logic, diagnostics, estimators, and other algorithms implemented in Simulink, Stateflow, System Composer, or MATLAB Function blocks.
Why use it?
It turns an algorithm idea into organized plans for the system, its architecture, implementation, and tests. This makes the intended behavior clearer before development begins.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/matlab/simulink-agentic-toolkit/specifying-mbd-algorithms
Any agent
npx skills add matlab/simulink-agentic-toolkit --skill specifying-mbd-algorithms
Clone the repo
git clone --depth 1 https://github.com/matlab/simulink-agentic-toolkit

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for specifying-mbd-algorithms

README.md
[![agentmods](https://agentmods.dev/badge/skills/matlab/simulink-agentic-toolkit/specifying-mbd-algorithms.svg)](https://agentmods.dev/skills/matlab/simulink-agentic-toolkit/specifying-mbd-algorithms)
Your own site
<a href="https://agentmods.dev/skills/matlab/simulink-agentic-toolkit/specifying-mbd-algorithms"><img src="https://agentmods.dev/badge/skills/matlab/simulink-agentic-toolkit/specifying-mbd-algorithms.svg" alt="Measured on agentmods" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,575 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00062 $0.01575
Opus 5 $0.00031 $0.00788
Sonnet 5 $0.00012 $0.00315
Haiku 4.5 $0.00006 $0.00158

Measured 4d ago against content hash 464eec93f7bf, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

specifying-mbd-algorithms scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills-catalog/model-based-design-core/specifying-mbd-algorithms/SKILL.md · 157 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 157 lines · 62 tokens per session scan A 464eec93f7bf

Subscribe to this mod's changes

specifying-mbd-algorithms is a skill published in the GitHub repository matlab/simulink-agentic-toolkit (1,035 stars, last pushed today), with no licence file. It adds 62 tokens to every session and 1,575 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

matlab-use-scenario-builder

Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder. sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface…

matlab/matlab-agentic-toolkit · 231 tokens

matlab-classify-tabular-data

Use this skill to classify tabular data end-to-end in MATLAB — load a dataset, prepare and clean it, select promising classifiers, train them, and compare accuracies with cross-validation, holdout, or hyperparameter optimization plus statistical tests. TRIGGER when: user asks to classify tabular data, pick classifiers…

matlab/matlab-agentic-toolkit · 165 tokens

matlab-fit-curve

Fit curves and surfaces interactively with the Curve Fitter app for a complete no-code fitting workflow. Invoke this skill when the Curve Fitter app, cftool, curveFitter, or "curve fitting tool/app" is mentioned in any way. Also use when exploring or comparing fit types (regression, interpolation, smoothing, splines…

matlab/matlab-agentic-toolkit · 121 tokens

matlab-use-machine-learning-apps

Use when the user wants to train, compare, or export machine learning models using Classification Learner or Regression Learner — including opening the app, loading data, training models, evaluating metrics, comparing results, visualizing plots, testing on held-out data, exploring model interpretability, and exporting…

matlab/matlab-agentic-toolkit · 85 tokens

roadrunner-convert-lanelet2-to-rrhd

Convert Lanelet2 maps (.osm) to RoadRunner HD Map (.rrhd) format using MATLAB. Use when converting Lanelet2 maps into RoadRunner Scene Builder, building driving scenes from open-source map data, or transforming road network definitions for simulation.

matlab/matlab-agentic-toolkit · 65 tokens

roadrunner-scenario-authoring

Programmatically author RoadRunner scenarios from MATLAB using roadrunnerAPI. Use when adding actors, creating routes, building scenario logic (phases, conditions, actions), placing vehicles/pedestrians, defining cut-in/crossing/ follow scenarios, or any programmatic scenario creation in RoadRunner. Triggers on…

matlab/matlab-agentic-toolkit · 100 tokens