skills/43-wentorai-research-plugins/skills/writing/latex/math-typesetting-guide/SKILL.md
LaTeX math typesetting, equation formatting, and cross-referencing
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research math-typesetting-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Comprehensive reference for typesetting mathematical notation, equations, and theorems in LaTeX with correct formatting, numbering, and cross-referencing.
\usepackage{amsmath} % Core math environments (align, gather, etc.)
\usepackage{amssymb} % Additional math symbols
\usepackage{amsthm} % Theorem environments
\usepackage{mathtools} % Extensions to amsmath (dcases, coloneqq, etc.)
\usepackage{bm} % Bold math symbols (\bm{x})
\usepackage{bbm} % Blackboard bold for indicators (\mathbbm{1})
\usepackage{nicefrac} % Inline fractions (\nicefrac{1}{2})
\usepackage{siunitx} % SI units (\SI{9.8}{m/s^2})
Use $...$ or \(...\) for math within text:
The loss function $\mathcal{L}(\theta) = -\sum_{i=1}^{N} \log p(y_i | x_i; \theta)$
minimizes the negative log-likelihood.
Use \[...\] for centered, unnumbered equations:
\[
\nabla_\theta \mathcal{L}(\theta) = -\frac{1}{N} \sum_{i=1}^{N}
\nabla_\theta \log p(y_i | x_i; \theta)
\]
Use the equation environment for numbered equations:
\begin{equation}
E = mc^2
\label{eq:einstein}
\end{equation}
Reference with \eqref{eq:einstein} to produce "(1)" with parentheses automatically.
Use align for multi-line equations with alignment points (&):
\begin{align}
\mathcal{L}(\theta) &= \mathbb{E}_{(x,y) \sim \mathcal{D}} \left[ \ell(f_\theta(x), y) \right] \label{eq:loss} \\
&= \frac{1}{N} \sum_{i=1}^{N} \ell(f_\theta(x_i), y_i) \label{eq:empirical-loss} \\
&\approx \frac{1}{B} \sum_{j=1}^{B} \ell(f_\theta(x_j), y_j) \label{eq:minibatch-loss}
\end{align}
Use align* for unnumbered multi-line equations. Use \nonumber to suppress numbering on specific lines.
Use split inside equation for a single equation number spanning multiple lines:
\begin{equation}
\begin{split}
\text{ELBO}(\theta, \phi; x) &= \mathbb{E}_{q_\phi(z|x)} \left[ \log p_\theta(x|z) \right] \\
&\quad - D_\text{KL}\left( q_\phi(z|x) \| p(z) \right)
\end{split}
\label{eq:elbo}
\end{equation}
For piecewise functions:
\begin{equation}
\text{ReLU}(x) =
\begin{cases}
x & \text{if } x > 0 \\
0 & \text{otherwise}
\end{cases}
\label{eq:relu}
\end{equation}
| Notation | LaTeX | Category |
|----------|-------|----------|
| Real numbers | \mathbb{R} | Sets |
| Integers | \mathbb{Z} | Sets |
| Natural numbers | \mathbb{N} | Sets |
| Expectation | \mathbb{E} | Probability |
| Probability | \mathbb{P} or \Pr | Probability |
| Normal distribution | \mathcal{N}(\mu, \sigma^2) | Distributions |
| Partial derivative | \frac{\partial f}{\partial x} | Calculus |
| Gradient | \nabla f | Calculus |
| Matrix transpose | \mathbf{A}^\top | Linear algebra |
| Matrix inverse | \mathbf{A}^{-1} | Linear algebra |
| Frobenius norm | \|\mathbf{A}\|_F | Linear algebra |
| L2 norm | \|\mathbf{x}\|_2 | Linear algebra |
| Inner product | \langle \mathbf{x}, \mathbf{y} \rangle | Linear algebra |
| Indicator function | \mathbbm{1}_{[condition]} | Functions |
| Summation | \sum_{i=1}^{N} | Operations |
| Product | \prod_{i=1}^{N} | Operations |
| Argmin/argmax | \operatorname*{argmin}_\theta | Optimization |
| KL divergence | D_\text{KL}(p \| q) | Information theory |
Define custom operators for clean notation:
% In preamble
\DeclareMathOperator*{\argmin}{arg\,min}
\DeclareMathOperator*{\argmax}{arg\,max}
\DeclareMathOperator{\Tr}{Tr} % Matrix trace
\DeclareMathOperator{\diag}{diag} % Diagonal matrix
\DeclareMathOperator{\softmax}{softmax}
\DeclareMathOperator{\sigmoid}{\sigma}
\newcommand{\R}{\mathbb{R}} % Shorthand for real numbers
\newcommand{\E}{\mathbb{E}} % Shorthand for expectation
\newcommand{\norm}[1]{\left\| #1 \right\|} % Norm shorthand
\newcommand{\abs}[1]{\left| #1 \right|} % Absolute value
\newcommand{\inner}[2]{\langle #1, #2 \rangle} % Inner product
% Matrix with parentheses
\begin{equation}
\mathbf{W} = \begin{pmatrix}
w_{11} & w_{12} & \cdots & w_{1n} \\
w_{21} & w_{22} & \cdots & w_{2n} \\
\vdots & \vdots & \ddots & \vdots \\
w_{m1} & w_{m2} & \cdots & w_{mn}
\end{pmatrix}
\end{equation}
% Matrix with square brackets
\begin{equation}
\mathbf{A} = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}
\end{equation}
% In preamble: define theorem environments
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{proposition}[theorem]{Proposition}
\newtheorem{corollary}[theorem]{Corollary}
\theoremstyle{definition}
\newtheorem{definition}[theorem]{Definition}
\theoremstyle{remark}
\newtheorem{remark}[theorem]{Remark}
% In document:
\begin{theorem}[Universal Approximation]
\label{thm:universal-approx}
For any continuous function $f: [0,1]^n \to \mathbb{R}$ and any
$\epsilon > 0$, there exists a feedforward neural network $g$ with
one hidden layer such that $\sup_{x \in [0,1]^n} |f(x) - g(x)| < \epsilon$.
\end{theorem}
\begin{proof}
The proof proceeds by construction. Consider a network with
$\sigmoid$ activation functions...
% End proof with QED symbol (automatic with amsthm)
\end{proof}
% Use cleveref for automatic reference formatting
\usepackage[capitalise,noabbrev]{cleveref}
% Then reference with:
\cref{eq:loss} % -> "Equation 1"
\cref{thm:universal-approx} % -> "Theorem 1"
\Cref{eq:loss} % -> "Equation 1" (capital, for start of sentence)
\crefrange{eq:loss}{eq:minibatch-loss} % -> "Equations 1 to 3"
% Label naming conventions:
% eq:name for equations
% thm:name for theorems
% lem:name for lemmas
% def:name for definitions
% fig:name for figures
% tab:name for tables
% sec:name for sections
\left( and \right) for auto-sizing delimiters, or explicit sizes: \big(, \Big(, \bigg(, \Bigg(\text{...} for words within math mode: $p(\text{data} | \theta)$\quad or \qquad for spacing in equations\phantom{x} for invisible spacing to align elements$$...$$ (plain TeX); use \[...\] or environments insteadtools
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