
algorithm-design
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.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/lingzhi227/agent-research-skills --skill algorithm-design- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads algorithm-design automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
- Define clear inputs and outputs
- Identify the main loop / recursive structure
- Specify all parameters and their types
- 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/\Ensurefor 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
FAQ
What does the algorithm-design skill do?
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.
How do I install algorithm-design?
Run npx skills add https://github.com/lingzhi227/agent-research-skills --skill algorithm-design in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/algorithm-design/ (personal) or .claude/skills/algorithm-design/ (project).
Which AI agents can use algorithm-design?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is algorithm-design safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains algorithm-design?
It is published by lingzhi227 in lingzhi227/agent-research-skills. It has 1,697 recorded installs.
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