lean-formal-feedback-loop

Coordinate Lean formal verification workflows to validate proofs against Rust outcomes.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/Dunc4nJ/agent-skills --skill lean-formal-feedback-loop
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lean-formal-feedback-loop
Source: https://github.com/Dunc4nJ/agent-skills/tree/main/skills/lean-formal-feedback-loop
Command: npx skills add https://github.com/Dunc4nJ/agent-skills --skill lean-formal-feedback-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Lean-Rust verification often suffers from drift between formal proofs and runtime behavior, causing hidden defects and misaligned conformance expectations. This skill orchestrates structured feedback loops, captures proof artifacts, and guides routing decisions to accelerate closure of formal assurance gaps.

Core Features & Use Cases

  • Coordinates intake, signal mining, frog ranking, and conformance checks across Lean and Rust surfaces.
  • Automates emission of proof-witness artifacts and conformance artifacts to support drift detection and regression testing.
  • Use Case: A team formalizing a Rust surface can cycle from initial proof friction to artifact-aligned closure with traceable decisions and reproducible lab seeds.

Quick Start

Follow the Quick Start to load frog candidates, mine project history, and build Lean baselines.

Frequently Asked Questions about lean-formal-feedback-loop

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

FAQPage Schema
How do I prevent drift between Lean formal proofs and Rust runtime behavior?

To prevent drift between Lean formal proofs and Rust runtime behavior, coordinate structured feedback loops that validate theorem statements against runtime outcomes. This workflow maintains formal artifacts and conformance gates to ensure end-to-end traceability from initial proof attempt to artifact emission.

What is the best way to automate Lean proof-witness artifact emission for conformance checks?

Automating Lean proof-witness artifact emission involves orchestrating intake, ranking, and routing workflows to extract witnesses and generate conformance artifacts. This supports drift detection and regression testing by capturing proof artifacts throughout the formal verification cycle.

How do I close formal assurance gaps when formalizing a Rust surface with Lean?

Closing formal assurance gaps when formalizing a Rust surface with Lean requires cycling from initial proof friction to artifact-aligned closure. You achieve this by loading frog candidates, mining project history, and building Lean baselines to guide routing decisions and traceable conformance checks.

Does this Lean formal verification workflow handle end-to-end loop requirements for witness extraction?

Yes, this Lean formal verification workflow satisfies end-to-end loop requirements for intake, ranking, routing, witness extraction, and artifact management. It coordinates these stages to align theorem statements with runtime behavior while maintaining formal artifacts.

Can I use this workflow for regression testing and drift detection across Lean and Rust surfaces?

Yes, you can use this workflow for regression testing and drift detection across Lean and Rust surfaces. It automates the emission of proof-witness artifacts and conformance artifacts specifically to support drift detection and ensure ongoing alignment between formal proofs and runtime behavior.