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.
82
78%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/matlab/SKILL.mdQuality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that covers all key dimensions thoroughly. It provides specific capabilities, comprehensive trigger terms spanning multiple scientific computing domains, explicit 'Use when' guidance, and a clear niche that distinguishes it from general programming or Python-based data science skills. The description is well-structured, concise yet comprehensive, and uses appropriate third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and domains: matrix operations, data analysis, visualization, scientific computing, linear algebra, signal processing, image processing, differential equations, optimization, statistics, scientific visualizations, syntax help, and code conversion between MATLAB and Python. | 3 / 3 |
Completeness | Clearly answers both 'what' (MATLAB/Octave numerical computing for matrix operations, data analysis, visualization, scientific computing) and 'when' (explicit 'Use when' clause covering writing scripts, specific domains, syntax help, and code conversion). Also includes a helpful note about execution environments. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'MATLAB', 'Octave', 'linear algebra', 'signal processing', 'image processing', 'differential equations', 'optimization', 'statistics', 'scientific visualizations', 'MATLAB syntax', 'convert between MATLAB and Python'. These are all terms users would naturally use when seeking help in this domain. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly occupies a distinct niche around MATLAB/GNU Octave specifically. The mention of specific tools (MATLAB, Octave), specific domains (signal processing, differential equations), and the MATLAB-Python conversion use case make it highly distinguishable from general programming or Python data science skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is well-structured with excellent progressive disclosure and fully actionable code examples, but it is far too verbose for its purpose. It essentially duplicates a MATLAB tutorial inline, covering basic syntax and concepts (loops, conditionals, anonymous functions, basic statistics) that Claude already knows, while the detailed reference files exist for exactly this purpose. The SKILL.md should be a lean overview pointing to references, not a comprehensive tutorial.
Suggestions
Drastically reduce inline content — remove sections on basic control flow, basic statistics functions, and elementary matrix creation that Claude already knows. Keep only the Quick Start, Common Patterns, Best Practices, and Reference Files sections.
Add validation/verification steps to the batch processing pattern (e.g., check file read success, validate output) and the numerical simulation pattern (e.g., check stability conditions).
Consolidate the 8 'Core Capabilities' subsections into brief 1-2 line descriptions with links to their respective reference files, rather than including full code examples that duplicate the reference content.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose, essentially serving as a MATLAB tutorial covering basic syntax, control flow, matrix creation, and plotting — all things Claude already knows. Much of this content (if/else syntax, for loops, anonymous functions, basic statistics functions) is redundant. The file is well over 200 lines of inline content that largely duplicates what's already in the referenced files. | 1 / 3 |
Actionability | The content provides fully executable, copy-paste ready code examples throughout — from running scripts, to matrix operations, plotting, ODE solving, and complete data analysis pipelines. Commands are specific and concrete. | 3 / 3 |
Workflow Clarity | The common patterns section shows reasonable multi-step workflows (data analysis pipeline, numerical simulation, batch processing), but there are no validation checkpoints or error recovery steps. The batch processing pattern notably lacks any verification that files were processed correctly. | 2 / 3 |
Progressive Disclosure | The skill has a clear overview structure with well-signaled, one-level-deep references to specific topic files (matrices-arrays.md, mathematics.md, graphics-visualization.md, etc.). The reference files section provides a clean navigation index. | 3 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
25e1c0f
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.