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Algorithm design

Skill dongzhigang13305312738-art/paper-skills/algorithm-design

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npx -y skills add dongzhigang13305312738-art/paper-skills --skill algorithm-design

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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.

SKILL.md

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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:

\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

classDiagram
    class Model {
        +forward(x: Tensor) Tensor
        +train_step(batch) float
    }

Sequence Diagram

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

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