drt-oracle

Detect inconsistencies between Lean formal models and production implementations via randomized testing.

5|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/nicholls-inc/claude-code-marketplace --skill drt-oracle
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: drt-oracle
Source: https://github.com/nicholls-inc/claude-code-marketplace/tree/main/crosscheck/skills/drt-oracle
Command: npx skills add https://github.com/nicholls-inc/claude-code-marketplace --skill drt-oracle

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It enables verification of the consistency between Lean formal models and their corresponding production implementations by detecting divergences through randomized testing.

Core Features & Use Cases

  • Differential Random Testing: Compares outputs of Lean models and production code on diverse inputs to identify discrepancies.
  • Automated Divergence Reporting: Generates detailed reports including minimized witnesses for reproduction.
  • Use Case: Engineers verifying formal specifications against production systems to ensure correctness before deployment.

Quick Start

Run the differential testing harness for the specified module to identify divergences between the Lean model and the implementation.

Frequently Asked Questions about drt-oracle

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect divergences between formal Lean models and production code?

You can detect divergences by running a differential random testing harness that generates diverse test inputs, executes both the Lean model and production implementation, and analyzes output differences to identify discrepancies.

What is differential random testing for formal verification workflows?

Differential random testing for formal verification compares outputs of Lean models acting as oracles against production code on varied inputs to identify inconsistencies and ensure software correctness before deployment.

How do I verify formal specifications against production implementations before deployment?

You verify formal specifications by executing automated differential tests that compare Lean oracle models against production implementations, generating detailed reports with minimized witnesses for any detected inconsistencies.

Can I use Lean models as oracles for automated divergence reporting?

Yes, Lean models can serve as oracles for automated divergence reporting, generating detailed reports that include minimized witnesses to help engineers reproduce and analyze detected inconsistencies.

Does divergence detection provide minimized witnesses for reproducing inconsistencies?

Yes, the divergence detection process generates detailed reports that include minimized witnesses, allowing engineers to easily reproduce and investigate the specific discrepancies found between the Lean model and production code.