matlab

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

Quality

86%

Does it follow best practices?

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Critical

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Quality

Content

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Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with executable examples and excellent progressive disclosure into verified reference files. The main gap is missing validation/error-recovery checkpoints in the batch processing and simulation workflows, which keeps workflow clarity capped.

Suggestions

Add explicit validation checkpoints to the Batch Processing pattern (e.g., check that readtable succeeded and handle empty/malformed files before combining results).

Include an error-recovery loop in the Numerical Simulation pattern for numerical stability (e.g., checking for NaN/Inf after time-stepping).

Trim the multi-platform Octave install instructions to a single line or move them to executing-scripts.md to improve conciseness.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with dense code examples and minimal over-explanation of concepts Claude already knows, though sections like the long Quick Start install block and Best Practices could be tightened slightly.	4 / 5
Actionability	Copy-paste ready executable code across all eight capability sections plus three end-to-end patterns, with specific commands (matlab -nodisplay, octave script.m) and concrete function calls covering common cases.	5 / 5
Workflow Clarity	Sequences are present in the patterns (load → clean → analyze → visualize → save), but batch and destructive operations like the Batch Processing and numerical simulation patterns lack explicit validation or error-recovery checkpoints, capping clarity at 3 per the destructive/batch guidance.	3 / 5
Progressive Disclosure	Clear overview structure with eight labeled sections each pointing to a one-level-deep reference file; all referenced files (matrices-arrays.md, mathematics.md, graphics-visualization.md, data-import-export.md, programming.md, python-integration.md, octave-compatibility.md, executing-scripts.md) are verified present in ./references/, and navigation is easy via the Reference Files list.	5 / 5
	Total	17 / 20 Passed

Description

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Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, comprehensive, and clearly answers both what the skill does and when to use it, with a distinct MATLAB/Octave niche. It could be slightly improved by adding the .m file extension as a natural trigger term.

Suggestions

Add the '.m' file extension as an explicit trigger term to match how users reference MATLAB/Octave files.

Include a synonym like 'scientific plots' or 'charts' alongside 'visualization' for broader natural-language coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions across matrix operations, linear algebra, plotting, data I/O, statistics, differential equations, and signal processing, plus code conversion between MATLAB and Python — comprehensive coverage of the domain.	5 / 5
Completeness	Explicitly answers what ('numerical computing for matrix operations, data analysis, visualization, and scientific computing') and when with two 'Use when...' clauses naming concrete trigger scenarios.	5 / 5
Trigger Term Quality	Strong natural keywords ('MATLAB/Octave scripts', 'linear algebra', 'signal processing', 'image processing', 'visualization') but lacks the .m file extension and some common synonyms a user might say, keeping it just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	Clear niche centered on MATLAB and GNU Octave with distinct language-specific triggers; minimal conflict risk with other coding skills since the language is named throughout.	5 / 5
	Total	19 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/coding/matlab/SKILL.md
Commit: 3a6c3a9

Reviewed: 1 day ago

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