paper2code
Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.
npx skills add PrathamLearnsToCode/paper2code --skill paper2code --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# paper2code — Orchestration You are executing the paper2code skill. This file governs the high-level flow. Each stage dispatches to a detailed reasoning protocol in `pipeline/`. Do NOT skip stages. Do NOT combine stages. Execute them in order. ## Parse arguments Extract from the user's input: - `ARXIV_ID`: the arxiv paper ID (e.g., `2106.09685`). Strip any URL prefix. - `MODE`: one of `minimal` (default), `full`, `educational`. - `FRAMEWORK`: one of `pytorch` (default), `jax`, `numpy`. If the user provided a full URL like `https://arxiv.org/abs/2106.09685`, extract the ID `2106.09685`. If the user provided a versioned ID like `2106.09685v2`, keep the version. ## Set up working directory Create a temporary working directory: `.paper2code_work/{ARXIV_ID}/` This is where intermediate artifacts go. The final output goes in the current directory under `{paper_slug}/`. ## Install dependencies Run via Bash: ```bash pip install pymupdf4llm pdfplumber requests pyyaml ``` ## Execute pipeline ### Stage 1 — Paper Acquisition and Parsing Read and follow: `pipeline/01_paper_acquisition.md` Run the helper script to fetch and parse the paper: ```bash python skills/paper2code/scripts/fetch_paper.p
- Parse arguments
- Set up working directory
- Install dependencies
- Execute pipeline
- Stage 1 — Paper Acquisition and Parsing
- Stage 2 — Contribution Identification
- Stage 3 — Ambiguity Audit
- Stage 4 — Code Generation
- Stage 5 — Walkthrough Notebook
- Cleanup
- Final output
- Mode-specific behavior
- Guardrails — always active
- Knowledge base — consult as needed
pip install pymupdf4llm pdfplumber requests pyyaml
python skills/paper2code/scripts/fetch_paper.py {ARXIV_ID} .paper2code_work/{ARXIV_ID}/
python skills/paper2code/scripts/extract_structure.py .paper2code_work/{ARXIV_ID}/paper_text.md .paper2code_work/{ARXIV_ID}/What does the paper2code skill do?
Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.
How do I install it?
Run `npx skills add PrathamLearnsToCode/paper2code --skill paper2code --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From PrathamLearnsToCode/paper2code, a repository with 1,468 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.