paper-to-code

SKILL.md

Paper to Code

Convert a research paper into a complete, runnable code repository.

Input

$0 — Paper PDF path, paper text, or paper URL

References

Paper2Code prompts (planning, analysis, coding stages): ~/.claude/skills/paper-to-code/references/paper-to-code-prompts.md

Workflow (from Paper2Code)

Stage 1: Planning

Four-turn conversation to create a comprehensive plan:

Overall Plan: Extract methodology, experiments, datasets, hyperparameters, evaluation metrics

Architecture Design: Generate file list, Mermaid classDiagram, sequenceDiagram

Task Breakdown: Logic analysis per file, dependency-ordered task list, required packages

Configuration: Extract training details into config.yaml

Stage 2: Analysis

For each file in the task list (dependency order):

Conduct detailed logic analysis

Map paper methodology to code structure

Reference the config.yaml for all settings

Follow the UML class diagram interfaces strictly

Stage 3: Coding

For each file in dependency order:

Generate code with access to all previously generated files

Follow the design's data structures and interfaces exactly

Reference config.yaml — never fabricate configuration values

Write complete code — no TODOs or placeholders

Stage 4: Debugging (if needed)

If execution fails:

Collect error messages

Identify root cause using SEARCH/REPLACE diff format

Apply minimal fixes preserving original intent

Re-run until successful

Output Structure

reproduced_code/
├── config.yaml        # Training configuration
├── main.py            # Entry point
├── model.py           # Model architecture
├── dataset_loader.py  # Data loading
├── trainer.py         # Training loop
├── evaluation.py      # Metrics and evaluation
├── reproduce.sh       # Run script
└── requirements.txt   # Dependencies

Key Constraints

Dependency order: Each file is generated with access to all previously generated files

Interface contracts: Mermaid diagrams serve as rigid interface definitions across all stages

No fabrication: Only use configurations explicitly stated in the paper

Complete code: Every function must be fully implemented

Rules

Follow the paper's methodology exactly — do not invent improvements

Generate code in dependency order (data loading → model → training → evaluation → main)

Use config.yaml for all hyperparameters and settings

Every class/method in UML diagram must exist in code

Generate a reproduce.sh script for one-command execution

If paper details are ambiguous, note them explicitly

Related Skills

Upstream: literature-search

Downstream: experiment-code

See also: code-debugging, algorithm-design