Claude Code Skills · page 83
Individual Claude Code skills mined from every repository in the directory: each SKILL.md, installable with one command, with its full definition and the repository's trust signals.
Diagnose MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or diagnosing runtime failures.
Deterministic workflow to download MATLAB Package Manager (mpm) and install MathWorks products from the OS command line with consistent, repeatable behavior. Use when installing MATLAB, Simulink, toolboxes, or support packages via command line, or setting up scripted installations for CI/CD, containers, or fleet provisioning.
Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation.
Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, assessing quality, or preparing code for handoff or publication.
Generate and run MATLAB unit tests using matlab.unittest and matlab.uitest. Parameterized tests, fixtures, mocking, coverage analysis, CI/CD with buildtool, app testing with gestures. Use when creating tests, writing test classes, running test suites, checking coverage, testing apps, or validating MATLAB code.
Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, filtering, sorting, cleaning, transforming, aggregating, smoothing, padding, trimming, and answering questions about data. MATLAB provides extensive, easy-to-use built-in functions for these workflows with no additional products required.
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Analyze the effective toolbox file set to produce a Dependency Manifest — classify all transitive dependencies as included, product, add-on, or external-unresolved, then present resolution options with tradeoffs. Use after matlab-define-toolbox-api when the spec is approved.
Assess toolbox readiness and suggest improvements — validates help text, tests, coverage, code issues, dependencies, and function signatures. Produces a punch list and can execute fixes via delegate skills on user approval. Use before packaging or when asked to improve a toolbox.
Execute the build plan — introspect buildfile.m, run its dependency chain, and produce the .mltbx toolbox package. Mechanical execution with no human checkpoint. Works with any buildplan shape.
Generate a MATLAB buildfile.m with tasks for static analysis, testing, coverage reporting, and packaging. Use after matlab-create-project when the project structure is in place and you need repeatable build automation.
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Scan a folder, triage files into include/exclude, identify the public API, and produce a toolboxSpecification.m Interface Spec — all in one pass. Use when turning loose code into a toolbox.
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Analyze a toolbox folder and generate a toolbox.ignore file — detects files that should not ship to end users based on what actually exists in the folder. Only suggests patterns for files found. Advisory: presents suggestions with reasons before writing.
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Guides the 7-step MATLAB memory optimization workflow: baseline, profile, identify, optimize, measure, verify, report. Use when asked to reduce MATLAB memory usage, find memory bottlenecks, fix out-of-memory errors, or optimize memory-intensive code.
Read BEFORE optimizing any MATLAB code for speed. Without this workflow, agents commonly optimize the wrong target, fabricate speedup claims without measurement, or introduce regressions. Guides the 7-step workflow: baseline, profile, identify, optimize, measure, verify, report.
Version-stamp, re-package, and distribute the .mltbx toolbox. Sets version in ToolboxOptions, re-runs packageToolbox, and guides distribution. Requires explicit user confirmation.
Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure execution time with statistical rigor, or use runperf.
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Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning timetable, truthlog, or converted table. For sensor data: builds task-oriented dataFormat structs (preferred) or objectDetection arrays (legacy). Use when importing flight logs, GPS logs, radar detections, IR measurements, lidar/camera bounding boxes, ADS-B data, AIS ship tracks, or any recorded data for use with trackers, filter tuning, or tracker evaluation.
Connects MATLAB to Databricks using JDBC drivers via Database Toolbox. Use when creating a JDBC connection to a Databricks cluster or SQL Warehouse, configuring Databricks authentication (PAT, OauthU2M, OauthM2M), selecting between Simba and OSS JDBC drivers, using databricks.JDBCConnection, StandaloneJDBCConnection, databricks.SQLWarehouse.connect(), or optimizing Databricks write performance.
Generates MATLAB Object Relational Mapping (ORM) code using Database Toolbox. Use when mapping MATLAB classes to database tables, reading/writing objects with ormread/ormwrite/ormupdate, defining Mappable classes, converting classes to SQL with orm2sql, or using object-oriented database workflows.
Reads data from relational databases using MATLAB Database Toolbox pushdown capabilities. Use when importing data from JDBC/ODBC databases, filtering rows, selecting columns, excluding duplicates, joining database tables, using sqlread, fetch, sqlinnerjoin, sqlouterjoin, databaseImportOptions, or rowfilter.
Generates MATLAB code for DuckDB database operations using Database Toolbox. Use when connecting to DuckDB (in-memory or file-based), querying CSV/Parquet/JSON/Excel files with SQL, creating development databases, preprocessing out-of-memory data, using duckdb(), installing DuckDB extensions, using DuckDB as an analytical engine in MATLAB, converting MATLAB analytics to SQL queries, optimizing data pipelines that use MATLAB file I/O before processing, or replacing file I/O bottlenecks with direct DuckDB reads.
Writes data from MATLAB to relational databases and performs database operations. Use when writing data with sqlwrite, updating rows with sqlupdate, executing SQL with execute, running stored procedures, managing transactions with commit/rollback, creating tables, or using SQL prepared statements.
S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).
Analyze antennas installed on electrically large conducting platforms using MATLAB Antenna Toolbox. Loads platform geometry from STL/STEP/IGES, installs antenna elements, selects electromagnetic solvers (MoM-PO, FMM, MoM), and computes patterns, impedance, coupling, and efficiency. Use when the user wants to model an antenna on a vehicle, aircraft, ship, satellite, or other large structure.
PDN DC voltage/current analysis, IR drop, design rule checking, and multi-net batch analysis on imported PCB layouts. TRIGGER: user asks about power integrity, PDN analysis, IR drop, voltage distribution, current density, power nets, or design rule checking on a PCB. Invoke BEFORE writing code — the PDN API chain is specialized and non-obvious. SKIP: importing a PCB file (use matlab-read-pcb-layout), EM field/S-parameter extraction (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), transmission line design (use matlab-design-pcb-txline).
Calculate and visualize monostatic and bistatic radar cross section (RCS) using MATLAB Antenna Toolbox. Computes RCS of platforms, antennas, and arrays with PO, MoM, and FMM solvers, supporting HH/VV/HV/VH polarization, GPU acceleration, and near-field observation. Use when the user wants to compute, plot, or analyze radar cross section.
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Analyze RF propagation and plan wireless sites using MATLAB Antenna Toolbox. Creates transmitter/receiver sites, computes signal strength, coverage maps, SINR, line-of-sight, and ray tracing in geographic or indoor environments. Supports multiple propagation models (free-space, close-in, Longley-Rice, ray tracing, rain/gas/fog), custom terrain, building data, and directional antennas. Use when the user wants to compute coverage, signal strength, path loss, SINR, ray tracing, or plan a wireless network.
Build custom PCB structures with pcbComponent, shapes, Boolean ops, feeds, and multi-layer stackups for non-catalog geometries. TRIGGER: user asks to build, modify, or customize a pcbComponent — add/remove shapes, edit polygons, place feeds, add metal layers, cut slots, or create non-catalog RF structures. Also when modifying geometry of an existing catalog-designed component (e.g., adding pads, removing elements, editing vertices). Invoke BEFORE writing pcbComponent code — layer/shape/feed API is non-obvious. SKIP: designing catalog components like filters/couplers/txlines (use the specific matlab-design-pcb-* skill), material/stackup definition only (use matlab-manage-pcb-material), EM analysis (use matlab-analyze-em), importing PCB files (use matlab-read-pcb-layout).
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Use AI-based antenna design exploration and 3D pattern reconstruction in MATLAB Antenna Toolbox. AIAntenna provides instant parametric sweeps of catalog antennas via pretrained surrogate models. patternFromAI reconstructs full 3D radiation patterns from two orthogonal 2D slices using AI. Use when the user wants rapid antenna design exploration, instant parameter tuning, or 3D pattern reconstruction from 2D measured/imported data.
Build custom antennas from geometric shapes using MATLAB Antenna Toolbox customAntenna. Creates arbitrary 2D and 3D antenna structures from shape primitives (shape.Rectangle, shape.Box, shape.Cylinder, etc.) with boolean operations, extrusion, substrate support, and feed creation. Use when the user wants to build a non-catalog antenna from scratch, create a custom geometry, import STL/CAD, or needs 3D structures like waveguides, horns, or cavities.
Create measuredAntenna objects from simulated or measured data using MATLAB Antenna Toolbox. Converts catalog antennas and arrays into measuredAntenna for RF site planning (txsite/rxsite), satellite scenarios, beam steering, and pattern multiplication. Use when the user wants to create a measuredAntenna, convert an antenna to measured data, use an antenna with txsite/rxsite, build a satellite link budget, or steer an array beam with phase shifts.
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Design impedance matching networks for antennas using MATLAB RF Toolbox matchingnetwork object. Synthesizes L/C topologies (L, Pi, Tee, 2-element, 3-element), ranks designs by return loss or gain, exports to circuit objects, and converts to distributed elements via Richards transformation. Supports antenna objects, sparameters, Touchstone files, and function handles as load impedance. Use when the user wants to match an antenna, design a matching network, improve return loss, or transform impedance.
Design and analyze antennas using MATLAB Antenna Toolbox. Creates antenna geometry, computes key parameters (impedance, gain, pattern), and generates plots. Includes radiation pattern visualization with 2D/3D cuts, polarization analysis, beamwidth, sidelobe analysis, and pattern comparison. Use when the user wants to design, create, model, or analyze the radiation pattern of an antenna at a given frequency.
Design and analyze finite and infinite antenna arrays using MATLAB Antenna Toolbox. Finite arrays include linear, rectangular, circular, and conformal types with beam steering, amplitude tapering, mutual coupling, and pattern visualization. Infinite arrays use Floquet boundary conditions for scan impedance, scan element pattern, and scan blindness detection. Use when the user wants to design, create, or analyze any antenna array (finite or infinite/periodic).
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Design PCB antennas using MATLAB Antenna Toolbox pcbStack. Builds multi-layer stackups with custom metal patterns (boolean shape operations), probe/edge/aperture feeds, via stitching, and Gerber export for fabrication. Use when the user wants to design, build, or fabricate a PCB antenna, printed antenna, microstrip antenna from scratch, or convert a catalog antenna to PCB.
Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).
Bandpass, lowpass, bandstop filter design — hairpin, coupled-line, combline, stub, SIW for frequency selection and harmonic rejection. TRIGGER: user asks to design, create, or analyze any RF filter (bandpass, lowpass, highpass, bandstop, hairpin, coupled-line, combline, stub, SIW). Invoke BEFORE writing code — filter class names differ from what you would guess. SKIP: EM simulation/S-parameter extraction of an existing filter (use matlab-analyze-em), general PCB layout assembly (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design).
Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interdigital capacitor, balun, resonator, phase shifter, or other passive RF component. Invoke BEFORE writing code — class names and property patterns are non-obvious. SKIP: filter design (use matlab-design-pcb-filter), coupler/splitter design (use matlab-design-pcb-coupler), transmission line design (use matlab-design-pcb-txline), EM analysis (use matlab-analyze-em), material setup only (use matlab-manage-pcb-material).
Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstrip, stripline, CPW, coplanar, differential pair), extract RLGC or per-unit-length parameters, compute trace impedance, analyze a PCB trace cross-section, or perform crosstalk/coupling analysis. Invoke BEFORE writing code — preferred over RF Toolbox analytical functions (txlineMicrostrip, txlineStripline, txlineCPW). SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), material/stackup definition only (use matlab-manage-pcb-material), building custom non-catalog geometry (use matlab-assemble-pcb-layout), optimization sweeps (use matlab-optimize-pcb-design).
Design reflectarray antennas and reconfigurable intelligent surfaces (RIS) using MATLAB Antenna Toolbox. Builds unit cells with pcbStack, characterizes reflection phase (S-curve) via planeWaveExcitation + infiniteArray + EHfields, synthesizes aperture phase distributions, builds physical geometry with conformalArray, and verifies patterns via pattern multiplication. Use when the user wants to design a reflectarray, RIS, intelligent reflecting surface, or periodic surface with phase control.
Design and analyze curved reflector antennas using MATLAB Antenna Toolbox. Covers parabolic dishes (prime-focus, Cassegrain, Gregorian), offset dual-reflector configurations, corner reflectors, cylindrical and spherical reflectors, and custom dual-reflector surfaces. Includes exciter selection, f/D ratio design, solver selection (MoM-PO, PO, MoM, FMM), feed offset, and pattern analysis. Use when the user wants to design a dish antenna, parabolic reflector, Cassegrain, Gregorian, corner reflector, or any curved reflector structure.
Estimate Specific Absorption Rate (SAR) of electromagnetic fields inside dielectric tissue phantoms using MATLAB Antenna Toolbox. Supports three approaches -- birdcage coil with volumetric Phantom (full tissue properties), conformalArray with shape.Custom3D (antenna outside tissue), and direct EHfields for implantable antennas (antenna inside tissue). Computes internal E-fields, calculates point and mass-averaged SAR, and validates via power balance. Use when the user wants to compute SAR, tissue absorption, or RF exposure from antennas near or inside biological tissue.
Export conversation MATLAB code to a clean, runnable .m script. Use when asked to save or export session work. TRIGGER: user asks to save, export, or generate a script from the current session's MATLAB code. Also when asked for a reproducible script or clean version of what was run.
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Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add lumped R/L/C, export S-parameters to Touchstone, or combine PCB elements into a circuit. Invoke BEFORE writing pcbcascade or circuit code — cascade rules and port matching are non-obvious. SKIP: designing individual components (use the specific matlab-design-pcb-* skill), EM analysis of a single component (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), optimization (use matlab-optimize-pcb-design).
Dielectric substrates, metal conductors, multi-layer stackups, and loss models (FR4, Rogers, Teflon) for RF PCB simulation. TRIGGER: user asks to set up a substrate, define dielectric properties, create a stackup, select a PCB material (FR4, Rogers, Teflon, etc.), or configure metal conductors. Invoke BEFORE writing dielectric() or metal() code — the API for named vs custom materials differs significantly. SKIP: PCB layout assembly (use matlab-assemble-pcb-layout), transmission line design (use matlab-design-pcb-txline), EM analysis (use matlab-analyze-em), importing a PCB file (use matlab-read-pcb-layout).
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Read and write 3-D point cloud data using Lidar Toolbox file I/O. Covers PLY, PCD, LAS/LAZ, PCAP (Velodyne/Ouster/Hesai), E57, and IDC (Ibeo) formats. Use when loading point clouds from disk, saving to disk, choosing the correct reader or writer for a file format, extracting or preserving lidar point attributes, reading Ibeo IDC sensor recordings, or converting between formats.
Register 3-D point clouds using ICP, NDT, LOAM, FGR, phase correlation, and CPD algorithms. Use when registering or aligning 3-D point clouds, choosing a registration algorithm, tuning registration parameters, preprocessing point clouds for registration or combining point clouds after registration.
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Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default patterns (Inputs:/Outputs: lists, block comments, uppercase See Also) produce non-conforming output. Use when writing, rewriting, fixing, or reviewing MATLAB help comments or function documentation.
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Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing time-domain voltage from PLL/VCO/clock simulations, measuring phase noise from variable-step solver output, computing jitter, or resampling non-uniform data.
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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 workflow; help choosing a fit type; and exporting to a figure, generating MATLAB code, fits to the workspace, and to Simulink Lookup Tables.
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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 Learner apps via AppController.
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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 MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.
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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 georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.
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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.
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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.
Build, modify, and diagram SimBiology models — API reference, helper functions, and layout patterns. Use when constructing or editing models programmatically or visually.
Fit SimBiology model parameters to data — fitproblem, population NLME, virtual patients, and NCA. Use when asked to fit, estimate, calibrate, or compute PK metrics.
Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters.
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