midnight-fact-check:fact-check-extraction

Extract testable claims from Midnight content into structured JSON with source references.

37|9|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/devrelaicom/midnight-expert --skill midnight-fact-check-fact-check-extraction
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: midnight-fact-check:fact-check-extraction
Source: https://github.com/devrelaicom/midnight-expert/tree/main/plugins/midnight-fact-check/skills/fact-check-extraction
Command: npx skills add https://github.com/devrelaicom/midnight-expert --skill midnight-fact-check-fact-check-extraction

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Extract verifiable statements from Midnight-related content to enable automated validation of claims about the Compact language, its APIs, and runtime behavior.

Core Features & Use Cases

  • Identify and extract testable claims from documentation, source code, and guides.
  • Produce a structured list of claims with precise source references and contexts for validation.
  • Support the midnight-fact-check pipeline by providing a standardized JSON schema for each claim.

Quick Start

Provide a content chunk and return a JSON array of claim objects following the described schema.

Frequently Asked Questions about midnight-fact-check:fact-check-extraction

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

FAQPage Schema
How do I extract testable claims from Midnight documentation for automated verification?

Extracting verifiable claims from Midnight docs involves identifying statements about the Compact language for validation against runtime or compiler behavior. The tool outputs a structured JSON array where each entry includes the exact claim text and a source object with file, line_range, and surrounding context.

What is claim extraction for ZKIR and Compact language validation?

Claim extraction for ZKIR and Compact language validation identifies testable assertions in documentation to check against runtime or compiler behavior. It bridges documentation and automated testing by producing a structured list of claims with precise source references and contexts.

How do I format Midnight documentation claims into a JSON array with source references?

Formatting Midnight documentation claims into a JSON array maps each identified claim to a structured object. This object includes the exact claim text alongside a source object containing the file, line_range, and surrounding context for clear traceability.

Can I use claim extraction on Midnight source code and guidance for type check validation?

You can apply claim extraction to Midnight source code and guidance. It identifies testable claims across these materials that can be validated through type checks, execution, compilation, or ZKIR analysis, returning a standardized JSON schema for each claim.

What is the best way to validate Compact language API claims from technical documentation?

The best way to validate Compact language API claims is extracting them into a structured JSON format with precise source references. This standardized schema enables automated pipelines to check the extracted claims against actual compiler behavior and runtime results.