Matlab Data Analysis
MATLAB R2026a data analysis workflow for tables, timetables, statistics, fitting, optimization-assisted analysis, visualization, report artifacts, and reproducible paper figures. Use whenever the user asks MATLAB to analyze data, plot results, fit models, process CSV/Excel/MAT files, or reproduce figures.
Install
$ agentstack add skill-wzyn20051216-matlab-agent-skills-matlab-data-analysis ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-wzyn20051216-matlab-agent-skills-matlab-data-analysis) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
MATLAB Data Analysis
Use this skill for MATLAB analysis pipelines that start with data and end with validated numbers, figures, or reports.
Workflow
- Inventory input files and schemas before coding.
- Load data with typed APIs:
readtable,readtimetable,matfile,datastore, or toolbox importers. - Normalize units, time zones, missing values, categorical fields, and outliers explicitly.
- Build analysis as functions plus a thin runner script.
- Save clean data, figures, and summary metrics under
artifacts/. - Validate with shape checks, range checks, and at least one numerical assertion.
API Preferences
- Tables and timetables for labeled data.
groupsummary,rowfun,varfun,synchronize, andretimefor structured transformations.fitlm,fitnlm,fitrgp,fitcsvm, orfitcensembleonly after checking toolbox availability.optimproblemor solver APIs for constrained fitting when simple regression is not enough.- Export figures with explicit size, resolution, and format.
Reproducible Figures
Every reproduced paper figure should include:
- Source data provenance.
- Script name and command used.
- Random seed if applicable.
- Axis labels, units, legend, and saved image path.
- A simple metric comparing reproduced result with reference when possible.
Validation
Use checks such as:
assert(height(T) > 0)
assert(all(isfinite(metrics.rmse)))
assert(isfile(fullfile(outDir, "figure_1.png")))Do not accept a plot as "done" unless the underlying numerical summary also looks sane.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: wzyn20051216
- Source: wzyn20051216/matlab-agent-skills
- License: MIT
- Homepage: https://github.com/wzyn20051216/matlab-agent-skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.