yaniv-golan

Proof Engine — AI skill for Claude Code

AI community

AI agent skill that creates formal, verifiable proofs of claims — every fact computed or cited, never asserted.

How to install Proof Engine

This entry records only its repository, not the path inside it, so there is no exact command to give. Open yaniv-golan/proof-engine and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Proof Engine does

AI agent skill that creates formal, verifiable proofs of claims — every fact computed or cited, never asserted.

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README

Proof Engine

[![Install in Claude Desktop](https://img.shields.io/badge/Install_in_Claude_Desktop-D97757?style=for-the-badge&logo=claude&logoColor=white)](https://proofengine.info/static/install-claude-desktop.html)

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![Agent Skills Compatible](https://img.shields.io/badge/Agent_Skills-compatible-4A90D9)](https://agentskills.io) [![Claude Code Plugin](https://img.shields.io/badge/Claude_Code-plugin-F97316)](https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/plugins) [![Cursor Plugin](https://img.shields.io/badge/Cursor-plugin-00D886)](https://cursor.com/docs/plugins)

An AI agent skill that verifies claims through code and live sources — not by asking the LLM to check itself. Every fact is either computed by Python code anyone can re-run or backed by a specific source, URL, and exact quote. The LLM never asserts a fact on its own authority.

Uses the open [Agent Skills](https://agentskills.io) standard. Works with Claude Desktop, Claude Cowork, Claude Code, Codex CLI, Cursor, Windsurf, Manus, ChatGPT, and any other compatible tool.

Why This Exists

LLMs hallucinate facts — and they hallucinate the checks on those facts. Ask an LLM to verify its own claim and it runs the same error-prone process again. The check is circular.

Proof Engine breaks the circle by routing every claim through a gate the LLM can't fake:

Computations are Python — Python doesn't hallucinate. If the LLM sets up the wrong calculation, the result is wrong in a visible, re-runnable way.
Citations are fetched and matched — the script hits the URL and searches for the quoted text on the live page. A fabricated citation fails the match; a partial match downgrades the verdict so the gap is visible.
9 hardening rules close the remaining escape routes — don't hand-type val