Agent skill · AI & Agents

lean-theorem-proving-guide

LLM agent for formal theorem proving in Lean 4

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill lean-theorem-proving-guide --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Path: skills/43-wentorai-research-plugins/skills/domains/math/lean-theorem-proving-guide/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Lean Theorem Proving Agent Guide ## Overview LeanAgent is an LLM-based agent for automated theorem proving in Lean 4, a modern proof assistant. It combines LLM reasoning with formal verification — proposing proof steps that are verified by Lean's type checker. Can prove novel theorems, not just benchmarks, by exploring proof strategies, backtracking on failures, and learning from successful proo

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About this skill
What does the lean-theorem-proving-guide skill do?

LLM agent for formal theorem proving in Lean 4

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill lean-theorem-proving-guide --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 brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 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.

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