Updated 2d ago
by matlab
matlab-agentic-toolkit
The MATLAB Agentic Toolkit brings proven MATLAB capabilities to AI agents, making engineering and scientific workflows agent-ready.
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- 30 skills (30 skills found in its SKILL.md files)
- 141 forks (141 forks)
- 2d ago last update (Last updated 2d ago)
Install
Skills CLI
npx skills add matlab/matlab-agentic-toolkit
Asks which skills and agents to install. Just one: npx skills add matlab/matlab-agentic-toolkit --skill matlab-compute-aerospace-environment — add -g for every project.
Claude Code
git clone https://github.com/matlab/matlab-agentic-toolkitcp -r "matlab-agentic-toolkit/skills-catalog/aerospace/matlab-compute-aerospace-environment" ~/.claude/skills/
Copies the matlab-compute-aerospace-environment skill into ~/.claude/skills/ for every project (use .claude/skills/ for one project). Repeat for the other skills listed below.
Plugin
/plugin marketplace add matlab/matlab-agentic-toolkit
Run inside Claude Code if the repository ships a plugin marketplace, then pick plugins from /plugin.
Skills can run code on your machine — read the SKILL.md first.
What it does
In the author's own words, from each skill's SKILL.md — showing the first 30 of 157 files.
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matlab-compute-aerospace-environment
Compute aerospace environment properties including atmosphere (ISA, COESA, NRLMSISE-00, non-standard, CIRA), gravity (spherical harmonic, WGS84, zonal, centrifugal), horizontal wind (HWM), magnetic field (WMM, IGRF), geoid height, geocentric radius, space weather data, planetary ephemeris, Earth orientation (polar motion, nutation, delta-UT1, CIP). Use when computing atmospheric density, temperat…
skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md on GitHub (opens in a new tab) -
matlab-convert-aerospace-coordinates
Perform aerospace unit conversions, time conversions, coordinate frame transformations, and rotation representations using Aerospace Toolbox. Use when converting units (length, velocity, angle, acceleration, angular velocity, force, mass, pressure, temperature, density), computing Julian dates or decimal years, transforming between coordinate frames (ECEF, ECI, LLA, flat Earth, geodetic/geocentri…
skills-catalog/aerospace/matlab-convert-aerospace-coordinates/SKILL.md on GitHub (opens in a new tab) -
matlab-analyze-reliability
Use this skill when fitting accelerated life models, computing mean time to failure (MTTF), B10 life and similar quantities, fitting life distributions like Weibull for reliability analysis, comparing distribution fits, computing confidence intervals on reliability quantities with bootstrapping, performing lifetime prediction, computing failure rates, plotting Kaplan-Meier curves, computing survi…
skills-catalog/ai-and-statistics/matlab-analyze-reliability/SKILL.md on GitHub (opens in a new tab) -
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 for a dataset, compare classifier accuracy, run cross-validation or a holdout e…
skills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md on GitHub (opens in a new tab) -
matlab-deploy-embedded-ai
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate…
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/SKILL.md on GitHub (opens in a new tab) -
matlab-engineer-tabular-features
Use when engineering or selecting the best features for single-response classification or regression in MATLAB, whatever the data's modality — for non-tabular data it routes extraction to a domain skill, then selects, assesses, and delivers on the resulting table. Not for multi-response problems, model training, or raw data acquisition.
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/SKILL.md on GitHub (opens in a new tab) -
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, custom equations); excluding outliers interactively; iterating on a fitting work…
skills-catalog/ai-and-statistics/matlab-fit-curve/SKILL.md on GitHub (opens in a new tab) -
matlab-import-external-ai-model
Import PyTorch, ONNX, or Keras 3 / TensorFlow 2.16+ deep learning models into MATLAB as dlnetwork objects. Use when importing .pt2 exported programs, traced .pt files, .onnx models, or Keras 3 models via matlabsaver. Covers importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromKeras, importNetworkFromTensorFlow, torch.export.export, PyTorchInputSizes, InputDataFormats, matlabsaver, tf…
skills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md on GitHub (opens in a new tab) -
matlab-interpret-machine-learning-model
Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the model made a specific prediction, including diagnosing predictions it got wrong; show how a predictor affects the output; and compare how the model behaves across cohorts or subgroups. Uses model-agnostic techniques and m…
skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model/SKILL.md on GitHub (opens in a new tab) -
matlab-train-network
Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simul…
skills-catalog/ai-and-statistics/matlab-train-network/SKILL.md on GitHub (opens in a new tab) -
matlab-use-experiment-manager
Create, modify, or delete experiments in Experiment Manager with live UI sync. TRIGGER when: user asks to create an experiment from code/script, wants to sweep parameters, asks to add/delete/edit experiments, or wants parameter changes reflected in the UI. Combines experiment creation (from code analysis) with frontend UI synchronization.
skills-catalog/ai-and-statistics/matlab-use-experiment-manager/SKILL.md on GitHub (opens in a new tab) -
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 trained models. Programmatic access to Classification Learner and Regression Le…
skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps/SKILL.md on GitHub (opens in a new tab) -
matlab-cosimulate-sumo-simulink
Build Simulink models that co-simulate with Eclipse SUMO traffic simulator. Use when creating SUMO-Simulink co-simulation, traffic simulation, TraCI connection, vehicle-in-the-loop testing, or ADAS scenario validation with SUMO. Covers Server/Client setup, Reader/Writer/Actor block configuration, random traffic generation, ego vehicle control, and SUMO file creation. Also use when the user mentio…
skills-catalog/automotive/matlab-cosimulate-sumo-simulink/SKILL.md on GitHub (opens in a new tab) -
matlab-import-driving-data
Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to…
skills-catalog/automotive/matlab-import-driving-data/SKILL.md on GitHub (opens in a new tab) -
matlab-use-ncap-protocol
Generate Euro NCAP test scenarios and variants using the ADT Euro NCAP support package. Use when creating NCAP seed scenarios, generating variants, translating between drivingScenario and RoadRunner, plotting scenario descriptors, computing NCAP scores, or exporting reports. Triggers on: ncapScenario, euroAssessment, getScenario, getScenarioDescriptor, generateVariants, ScenarioDescriptor, Scenar…
skills-catalog/automotive/matlab-use-ncap-protocol/SKILL.md on GitHub (opens in a new tab) -
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 extraction, 3D asset generation, static-object placement, point-cloud georeferencin…
skills-catalog/automotive/matlab-use-scenario-builder/SKILL.md on GitHub (opens in a new tab) -
roadrunner-asset-mapping
RoadRunner asset path lookup tables for map format conversions in MATLAB. Maps lane markings, signs, signals, barriers, objects, and lane types to RoadRunner asset paths. Use when converting map formats to RRHD, resolving asset paths, or assigning visual assets to HD Map objects.
skills-catalog/automotive/roadrunner-asset-mapping/SKILL.md on GitHub (opens in a new tab) -
roadrunner-build-scenario-from-osc
Build a RoadRunner Scenario programmatically from an OpenSCENARIO 1.x (.xosc) file using the `roadrunner-scenario-authoring` skill. Use when the user wants to recreate a scenario from a .xosc file, interpret an OpenSCENARIO file and build it programmatically, reconstruct a .xosc as a RoadRunner scenario, generate a MATLAB script from a .xosc file, or convert an OpenSCENARIO file to MATLAB code. D…
skills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md on GitHub (opens in a new tab) -
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.
skills-catalog/automotive/roadrunner-convert-lanelet2-to-rrhd/SKILL.md on GitHub (opens in a new tab) -
roadrunner-core
Foundation skill for all RoadRunner workflows: MATLAB path setup, connection, project/scene/scenario lifecycle, world settings, handle management, status, and close. Use when connecting to RoadRunner, managing projects/scenes/scenarios, setting world origin, checking status, closing RoadRunner, or when any downstream RoadRunner skill needs initialization.
skills-catalog/automotive/roadrunner-core/SKILL.md on GitHub (opens in a new tab) -
roadrunner-import-scene
Import HD Map or OpenDRIVE files into a RoadRunner scene using MATLAB. Use when loading driving scenes in RoadRunner or RoadRunner Scene Builder, importing RRHD, OpenDRIVE, or other RoadRunner-supported formats for simulation, or verifying Lanelet2-to-RRHD conversion results visually. Requires rrApp handle from roadrunner-core.
skills-catalog/automotive/roadrunner-import-scene/SKILL.md on GitHub (opens in a new tab) -
roadrunner-rrhd-authoring
Build RoadRunner HD Map entities in MATLAB — lanes, boundaries, markings, junctions, signs, signals, barriers, parking. Use when creating driving scenes from scratch, authoring road networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources.
skills-catalog/automotive/roadrunner-rrhd-authoring/SKILL.md on GitHub (opens in a new tab) -
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: roadrunnerAPI, scenario authoring, add actor, create route, phase logic, cut-in scena…
skills-catalog/automotive/roadrunner-scenario-authoring/SKILL.md on GitHub (opens in a new tab) -
roadrunner-scenario-simulating
Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation…
skills-catalog/automotive/roadrunner-scenario-simulating/SKILL.md on GitHub (opens in a new tab) -
matlab-share-content
Share MATLAB content by guiding users through uploading to GitHub, MATLAB Drive, or File Exchange, then generating "Open in MATLAB Online" URLs. Covers the full sharing workflow: choosing a platform, uploading content (automated via gh CLI for GitHub, manual for MATLAB Drive and File Exchange), and constructing the correct URL. Use when a user wants to share MATLAB code with others, open local fi…
skills-catalog/cloud-solutions/matlab-share-content/SKILL.md on GitHub (opens in a new tab) -
matlab-deploy-ai-model
Generate C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. Covers PyTorch ExportedProgram (.pt2) via loadPyTorch…
skills-catalog/code-generation/matlab-deploy-ai-model/SKILL.md on GitHub (opens in a new tab) -
matlab-deploy-embedded-code
Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL v…
skills-catalog/code-generation/matlab-deploy-embedded-code/SKILL.md on GitHub (opens in a new tab) -
matlab-generate-code
Generate, verify, refine, and accelerate C/C++ or CUDA code from MATLAB with MATLAB Coder, Embedded Coder, GPU Coder, or MATLAB Test. Also covers writing codegen-ready MATLAB code: language constraints, coder.* directives, and optimization patterns. Triggers on: codegen, MEX, deploy MATLAB as C/C++, GPU Coder, coder.screener, coder.config, coder.gpuConfig, coder.typeof, coder.runTest, matlabtest.…
skills-catalog/code-generation/matlab-generate-code/SKILL.md on GitHub (opens in a new tab) -
matlab-optimize-gpu-codegen
Optimize MATLAB design files for GPU Coder to generate faster CUDA code. Iteratively profiles, rewrites, and benchmarks until performance targets are met or diagnostics are resolved. Use when asked to: optimize for GPU Coder, improve GPU codegen performance, profile generated GPU/CUDA code, profile GPU MEX, fix gpuPerformanceAnalyzer diagnostics, speed up GPU MEX, reduce GPU memory transfers, imp…
skills-catalog/code-generation/matlab-optimize-gpu-codegen/SKILL.md on GitHub (opens in a new tab) -
matlab-review-fi-object-code
Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code.
skills-catalog/code-generation/matlab-review-fi-object-code/SKILL.md on GitHub (opens in a new tab)
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Review before you install
A skill is a set of instructions and scripts your agent will follow, and it can run code on your machine. Read the SKILL.md and any scripts first — this listing is not a security review.