Claude For Researchers

Claude for Researchers

A practical guide and toolkit for researchers — especially physicists and mathematicians — who want to use [Claude Code](https://claude.ai/code) productively on long, technically demanding projects.

This guide is written from real experience running a months-long mathematical research project with Claude Code, not a weekend experiment. It covers what works, what wastes time, the failure modes you will hit, and how to set up a workflow that survives them.

**What this guide is not.** There are other projects focused on getting Claude to *conduct* research autonomously — literature surveys, hypothesis generation, paper drafting. This is not that. The goal here is to give you a well-structured workspace and a reliable workflow so that *you* can do the research faster and more cleanly: less time on housekeeping, better continuity across sessions, fewer mistakes from working in a big messy codebase. Claude is the tool; you are the researcher.

**Version 2026.09 · v1.16.0** — see [CHANGELOG.md](CHANGELOG.md) for recent updates. If you set up a project from an earlier copy, the changelog tells you what is worth re-copying from `starter/`. (The calendar tag says how current your copy is; the SemVer says how much has changed and whether anything breaks — see the changelog intro.)

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How to read this guide

This guide serves two audiences at once, so it is organised in parts:

• Never used Claude Code? Read Part I from the top. It takes you from nothing to a fully configured project — including a step where Claude does the setup for you. Then read Part II gradually, as the topics become relevant to your work. You do not need anything in Part III to be productive.
• Already using Claude Code? Skip Part I (except perhaps Bootstrapping, which is useful for any new project) and start with Part II — the workflow patterns there ar