Convert an ML research paper into a complete, runnable code repository. 3-stage pipeline from Paper2Code — Planning (UML + dependency graph) → Analysis (per-file logic) → Coding (dependency-ordered generation). Use for reproducing paper methods.
Quickly install paper-to-code AI skill to your development environment via command line
Source: lingzhi227/claude-skills.
Convert a research paper into a complete, runnable code repository.
Stage 1: Planning Four-turn conversation to create a comprehensive plan:
Stage 2: Analysis For each file in the task list (dependency order):
Convert an ML research paper into a complete, runnable code repository. 3-stage pipeline from Paper2Code — Planning (UML + dependency graph) → Analysis (per-file logic) → Coding (dependency-ordered generation). Use for reproducing paper methods. Source: lingzhi227/claude-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/lingzhi227/claude-skills --skill paper-to-codeConvert an ML research paper into a complete, runnable code repository. 3-stage pipeline from Paper2Code — Planning (UML + dependency graph) → Analysis (per-file logic) → Coding (dependency-ordered generation). Use for reproducing paper methods. Source: lingzhi227/claude-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/lingzhi227/claude-skills --skill paper-to-code Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/lingzhi227/claude-skills