lean-formalize

lean-formalize is a skill for Claude Code from wanshuiyin/Auto-claude-code-research-in-sleep. It costs 81 tokens per session (4,200 once invoked), scanned A, original, MIT.

A workflow for writing and checking mathematical proofs in Lean, a programming language and proof checker for formal mathematics.

In plain words
What is it for?
Use it to formalize a theorem, continue an incomplete Lean project, or audit whether an existing proof establishes the intended claim.
Why use it?
It tests whether the original mathematical statement is actually proved and whether the proof's intermediate steps and assumptions connect correctly.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Claude Code; mentions Codex.

Part of the aris plugin — 84 skills, 1 command shipped together

Good fit Use it to formalize a theorem, continue an incomplete Lean project, or audit whether an existing proof establishes the intended claim.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize
About the project

ARIS is a collection of Markdown-based skills that define a workflow for autonomous machine-learning research, including idea discovery, experiment automation, and review loops. Researchers and AI coding agents use it across tools such as Claude Code, Codex, Cursor, and OpenClaw without depending on a single framework. The catalogue entries are ARIS workflow skills and agents.

wanshuiyin/Auto-claude-code-research-in-sleep · 17,059 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill lean-formalize
Clone the repo
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep

Made for: Claude Code.

Or install aris, the plugin that ships this one along with the rest of its 84 skills, 1 command.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lean-formalize

README.md
[![agentmods](https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize/github.svg)](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize)
Your own site
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for lean-formalize

Your own site · 80×15
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/lean-formalize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,200 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00081 $0.04200
Opus 5.5 $0.00032 $0.01680
Sonnet 5.5 $0.00016 $0.00840
Haiku 4.5 $0.00008 $0.00420

Measured today against content hash 14f18d5314b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lean-formalize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/lean-formalize/SKILL.md · 364 lines

How it starts

The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lean Formalize

Turn the user's mathematical statement into a checked Lean theorem with its meaning preserved. A compiled conditional lemma is progress; completion concerns the original statement and the trust basis actually used.

When to use Lean

Use this skill when the user requests Lean, when continuing an existing Lean proof, or when formal verification addresses a concrete uncertainty in a central claim—for example, a long dependency chain, a delicate reduction, or coverage of a finite classification. State the obligation it will help resolve and proceed within the authorized task. Difficulty alone is not a reason to formalize. Ordinary derivations and short proofs can stay in formula-derivation or proof-writer; do not make Lean a prerequisite for every mathematical result. Respect the user's chosen proof method and the scale of the requested work.

Core workflow

Original statement and Lean definitions
  → A: cross-family adversarial statement alignment
  → Proof obligations, representations, and lemma interfaces
  → Lean implementation ↔ B: adversarial review of key arguments and connections
  → Actual inputs connected; original theorem assembled
  → Executed type, definition, and transitive-axiom audit
  → C: cross-family adversarial review of the final exported result
  → Reproducible delivery and research-state update

For substantial new proof projects, A/B/C are part of the workflow. For a continuation, reuse completed checks on unchanged claims and revisit affected ones. Small routine formalizations need checks proportional to the actual claim; an explicit user request for cross-family review still applies to them.

Use the authorized reviewer families available in the current host. If the user specifies both Grok and Gemini, obtain and record both; a same-family agent or another provider does not silently satisfy either request. Unavailability leaves that checkpoint pending while independent proof work continues. A checked theorem and a fully completed requested review workflow are separate deliverables.

Read the full file on GitHub · 364 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 364 lines · 81 tokens per session scan A 14f18d5314b7

Subscribe to this mod's changes

lean-formalize is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (17,059 stars, last pushed yesterday), licensed MIT. It adds 81 tokens to every session and 4,200 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-07.

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