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informal-spec

Generate natural language specifications for software modules from Dafny code.

5|Updated Mar 4, 2026
Search Tags:#verification#formal specification#prose extraction#lean pipeline#module boundary
One-click install
npx skills add https://github.com/nicholls-inc/claude-code-marketplace --skill informal-spec
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: informal-spec
Source: https://github.com/nicholls-inc/claude-code-marketplace/tree/main/crosscheck/skills/informal-spec
Command: npx skills add https://github.com/nicholls-inc/claude-code-marketplace --skill informal-spec

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps developers and engineers produce precise, unambiguous natural language specifications for software modules, facilitating formal verification and automated translation into Lean.

Core Features & Use Cases

  • Specification Extraction: Generate detailed, human-readable prose specifications from invariants, Dafny code, or combined signatures with user intent.
  • Design Validation: Support rigorous module boundary and pre/postcondition analysis, reducing misunderstandings and misinterpretations.
  • Use Case: Use this Skill to produce a formal, sign-off-ready spec for a numerical library component to help automate verification workflows.

Quick Start

Provide the module's Dafny code or design documents, and this Skill will generate a detailed natural language spec suitable for formal tools and peer review.

Frequently Asked Questions about informal-spec

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

FAQPage Schema
How do I extract natural language specifications from Dafny code for formal verification?▼

You can extract natural language specifications by providing Dafny code or design documents to generate detailed, unambiguous prose covering invariants, preconditions, postconditions, and edge cases for formal verification workflows.

What is the best way to write module boundary definitions for a Lean pipeline?▼

Writing module boundary definitions for a Lean pipeline involves producing strict, unambiguous natural language prose specifications that capture preconditions, postconditions, and invariants for downstream translation into Lean.

Can I use Dafny code and user intent to generate sign-off ready specifications?▼

Yes, you can use Dafny code combined with user intent to generate formal, sign-off ready natural language specifications suitable for peer review and automated formal methods translation.

How do I validate preconditions and postconditions to reduce design misunderstandings?▼

Validating preconditions and postconditions requires rigorous module boundary analysis using natural language specifications to ensure unambiguous communication among developers and reduce design misinterpretations.

Does generating prose specifications work for numerical library components requiring formal methods?▼

Generating prose specifications works effectively for numerical library components by producing comprehensive natural language specs that enable formal verification and automated translation into Lean.

What format should invariants and edge cases follow for downstream translation to Lean?▼

Invariants and edge cases should follow a strict, unambiguous natural language prose format that comprehensively defines module boundaries and conditions for accurate downstream translation to Lean.

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