MATLAB

Avoid common MATLAB mistakes — indexing traps, matrix vs element-wise ops, and vectorization pitfalls.

Security Scan

This is an instruction-only MATLAB cheat-sheet that only requires the matlab binary and otherwise makes no unusual or disproportionate requests.

Purpose & Capability

Name/description match the SKILL.md content (MATLAB pitfalls). Declaring the matlab binary requirement is proportionate and expected.

Instruction Scope

SKILL.md is static guidance (indexing, operators, debugging tips). It does not instruct the agent to read unrelated files, access environment variables, or transmit data externally.

Install Mechanism

No install spec or external downloads; instruction-only skills have minimal disk/write risk.

Credentials

No environment variables, credentials, or config paths are requested — nothing disproportionate is asked for.

Persistence & Privilege

always is false and the skill is user-invocable. Allowing autonomous invocation is the platform default and acceptable given the skill's limited scope.

Assessment

This skill is a read-only MATLAB tipsheet and does not request secrets or perform installations. It will only be useful if you have the matlab binary available. Because the skill’s source is unknown, consider: (1) only enable it if you trust the registry publisher or prefer local documentation; (2) confirm you want an agent to be able to call it autonomously (it’s low-risk but will run if invoked); and (3) if you need reproduction from a vetted source, consult official MathWorks documentation instead.

Indexing

• 1-based indexing — first element is A(1), not A(0)
• end keyword for last index — A(end), A(end-1), works in any dimension
• Linear indexing on matrices — A(5) accesses 5th element column-major order
• Logical indexing returns vector — A(A > 0) gives 1D result regardless of A's shape

Matrix vs Element-wise

• * is matrix multiplication — .* for element-wise
• / solves A*x = B — ./ for element-wise division
• ^ is matrix power — .^ for element-wise power
• Forgetting the dot is silent bug — dimensions might accidentally match

Vector Shape Matters

• Row vector: [1 2 3] or [1, 2, 3] — shape is 1×3
• Column vector: [1; 2; 3] — shape is 3×1
• Transpose with ' (conjugate) or .' (non-conjugate) — for complex, they differ
• * between row and column gives scalar or matrix — depending on order

Array Preallocation

• Growing arrays in loops is slow — preallocate: A = zeros(1000, 1)
• zeros, ones, nan for preallocation — specify size upfront
• Cell arrays: cell(n, m) — preallocate cells too

Broadcasting

• Implicit expansion since R2016b — A + b works if dimensions compatible
• Singleton dimensions expand — [1;2;3] + [10 20] gives 3×2
• Before R2016b needed bsxfun — legacy code may still use it

NaN Handling

• NaN ~= NaN is true — use isnan() to check
• Most operations propagate NaN — sum([1 NaN 3]) is NaN
• Use 'omitnan' flag — sum(A, 'omitnan'), mean(A, 'omitnan')

Cell Arrays vs Matrices

• {} for cell arrays — hold mixed types, different sizes
• () indexing returns cell — C(1) is 1×1 cell
• {} indexing extracts content — C{1} is the actual value
• Comma-separated list from C{:} — useful for function arguments

Common Mistakes

• = for assignment, == for comparison — if x = 5 is error in MATLAB
• Semicolon suppresses output — forget it and flood command window
• clear removes all variables — use clearvars for selective, close all for figures
• i and j are imaginary unit — don't use as loop variables, or reassign explicitly
• String vs char: "text" vs 'text' — double quotes are string arrays (R2017a+)

Functions

• Anonymous functions: f = @(x) x^2 — quick inline functions
• Multiple outputs: [a, b] = func() — must capture or use ~ to ignore
• nargin/nargout for optional args — check how many inputs/outputs provided
• varargin/varargout for variable args — cell array of extra arguments

Debugging

• dbstop if error — breakpoint on any error
• keyboard in code pauses execution — enter debug mode at that line
• whos shows variable sizes — size(A) for specific variable