Algorithm Design

by lingzhi2279e6c085d65e3No license386 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 7 months ago

Design algorithms with LaTeX pseudocode and UML diagrams. Generate algorithmic environments, Mermaid class/sequence diagrams, and ensure consistency between pseudocode and implementation. Use when formalizing methods for a paper.

AI-generated overview

Formalizes methods into LaTeX algorithm pseudocode and Mermaid UML diagrams, checking consistency with code.

What it does
Turns a method description or implementation into formal algorithm pseudocode written with LaTeX algorithm and algpseudocode environments, including inputs, outputs, parameters and numbered steps. It also produces Mermaid class and sequence diagrams for the system architecture. Finally it verifies that pseudocode steps, UML classes and parameter names match the implementation.
When to use it
Use when formalizing a method for a paper or technical write-up that needs standard algorithmic notation. It suits work where pseudocode and architecture diagrams must stay consistent with existing code.
Requirements
Needs LaTeX with the algorithm and algpseudocode packages for the pseudocode output, and Mermaid support for the diagrams. It reads a bundled reference file of algorithm and diagram templates. No scripts are shipped; instructions only.

Algorithm Design

Formalize methods into algorithm pseudocode and system architecture diagrams.

Input

  • $0 — Method description or implementation to formalize

References

  • Algorithm and diagram templates: ~/.claude/skills/algorithm-design/references/algorithm-templates.md

Workflow

Step 1: Formalize the Algorithm

  1. Define clear inputs and outputs
  2. Identify the main loop / recursive structure
  3. Specify all parameters and their types
  4. Write step-by-step pseudocode

Step 2: Generate LaTeX Pseudocode

Use algorithm + algpseudocode environments:

latex
\begin{algorithm}[t]\caption{Method Name}\label{alg:method}\begin{algorithmic}[1]\Require Input $x$, parameters $\theta$\Ensure Output $y$\State Initialize ...\For{$t = 1$ to $T$}    \State $z_t \gets f(x_t; \theta)$    \If{convergence criterion met}        \State \textbf{break}    \EndIf\EndFor\State \Return $y$\end{algorithmic}\end{algorithm}

Step 3: Generate UML Diagrams (Mermaid)

Class Diagram
mermaid
classDiagram    class Model {        +forward(x: Tensor) Tensor        +train_step(batch) float    }
Sequence Diagram
mermaid
sequenceDiagram    participant M as Main    participant D as DataLoader    M->>D: load_data()    D-->>M: batches

Step 4: Verify Consistency

  • Every pseudocode step must map to a code module
  • Every class in the UML must exist in the implementation
  • Parameter names must match between pseudocode and code

Rules

  • Use standard algorithmic notation (not code syntax)
  • Number lines for easy reference
  • Include complexity analysis as a comment or proposition
  • Use \Require / \Ensure for inputs/outputs
  • Keep pseudocode at the right abstraction level — not too detailed, not too vague

Related Skills

  • Upstream: atomic-decomposition, math-reasoning
  • Downstream: experiment-code, paper-writing-section
  • See also: symbolic-equation

Source and attribution

Source:lingzhi227/agent-research-skillsinskills/algorithm-designat commit9e6c085

License: No license

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