CoqPyt: Proof Navigation in Python in the Era of LLMs
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Abstract (arXiv)
Proof assistants enable users to develop machine-checked proofs regarding software-related properties. Unfortunately, the interactive nature of these proof assistants imposes most of the proof burden on the user, making formal verification a complex, and time-consuming endeavor. Recent automation techniques based on neural methods address this issue, but require good programmatic support for collecting data and interacting with proof assistants. This paper presents CoqPyt, a Python tool for interacting with the Coq proof assistant. CoqPyt improves on other Coq-related tools by providing novel features, such as the extraction of rich premise data. We expect our work to aid development of tools and techniques, especially LLM-based, designed for proof synthesis and repair. A video describing and demonstrating CoqPyt is available at: https://youtu.be/fk74o0rePM8.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 May 2024.
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Citing papers per year: 2024: 1; 2025: 3; 2026: 1.
5 papers.
- 2024Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verificationcited by 25
- 2025Agentic Verification of Software Systemscited by 5
- 2025PAT-Agent: Autoformalization for Model Checkingcited by 3
- 2026Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repaircited by 3
- 2025ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Provingcited by 1
- 2026Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair17 May 2026
- 2025Agentic Verification of Software Systems21 Nov 2025
- 2025PAT-Agent: Autoformalization for Model Checking28 Sep 2025
- 2025ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving7 Feb 2025
- 2024Rango: Adaptive Retrieval-Augmented Proving for Automated Software Verification18 Dec 2024