Op

OpenATP: A platform for automated theorem proving in Lean

Hacker News

OpenATP: A platform for automated theorem proving in Lean

TL;DR: I created a Python package to make running agentic automated theorem provers (e.g., Aristotle, Numina-Lean-Agent, Claude Code, etc...) as simple as open-atp prove Lemma.lean result/ claude I took a class on formal verification back in 2022 when I was an undergraduate. There was something incredibly satisfying about constructing proofs in Coq and knowing my statements were now formally verified. However, formal methods were so time consuming that they weren't practical in most industry settings. The rise of AI has changed that story: https://blog.janestreet.com/formal-methods-at-jane-street-in... . AI is producing algorithms and mathematical proofs far faster than humans can review them and formal methods offer a solution. Automated theorem provers take a statement formalized in a proof assistant like Lean and attempt to supply a proof. Unlike natural language proofs, these proofs can be machine-checked, reducing the burden of review on humans. AI agents are powerful automated theorem provers. Even general purpose coding agents, like Claude Code, can be effective provers with the right skills and tooling. However, these methods are currently challenging to run. They require configuring Docker containers with the proper Lean environment and agent tooling (skills, plugins, MCP, credentials). Furthermore, there is not a common interface to existing provers. OpenATP aims to solve both of these challenges! It makes it easy to run methods locally in Docker or remotely in Modal. It currently supports the following provers: https://open-atp.henryrobbins.com/en/latest/provers/index.ht... .

Share card

Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, agent · Missing: macos, cursor, model
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: supports, created · Missing: reddit linkedin, podcasting, latex
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Vital Lean Keto
Vital Lean Keto21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vital Lean Keto

Indie Hackerscommitment-full-time
Mi
Micro-Lean: Lean Without the Bullshit32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Micro-Lean: Lean Without the Bullshit

Hacker News1
Fo
Formalizing Principia Mathematica using Lean36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Formalizing Principia Mathematica using Lean

Hacker News188
Th
The Lean Startup DIAMOND33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Lean Startup DIAMOND

Hacker News1
Le
Lean Canvas AI25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lean Canvas AI

Hacker News3
Th
The Lean Party40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Lean Party

Hacker News4
Retro Lean Forskolin
Retro Lean Forskolin17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Retro Lean Forskolin

Indie Hackerscommitment-side-project
Th
The Lean Roadmap31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Lean Roadmap

Hacker News2
Shopsys Framework
Shopsys Framework43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lean Platform for Online Stores

Indie Hackerscommitment-full-time
Le
Lean Canvas generator32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lean Canvas generator

Hacker News4