validate

Fact-check textual drafts against a centralized DataStore repository.

10|1|Updated Jun 29, 2026

Search Tags:#validation #verification #risk-assessment #data-integrity #fact-check #content-audit

Ready to run

npx skills add https://github.com/mishahanin/heading-os --skill validate-mishahanin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: validate
Source: https://github.com/mishahanin/heading-os/tree/main/.claude/skills/validate
Command: npx skills add https://github.com/mishahanin/heading-os --skill validate-mishahanin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates factual errors and inconsistencies in drafts by cross-referencing content against a verified source-of-truth repository.

Core Features & Use Cases

Forensic Claim Extraction: Automatically identifies explicit and implicit claims, including numbers, dates, and superlatives.
Hierarchical Validation: Grades claims as Validated, Unverified, or Contradicted based on a strict source-of-truth hierarchy.
Risk Assessment: Assigns risk levels to unverified claims to prioritize manual review for financial, legal, or investor-facing documents.

Quick Start

Run the validate skill by providing the file path to your draft document to receive a comprehensive forensic report.

Frequently Asked Questions about validate

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

FAQPage Schema

How do I fact-check a proposal draft against a source-of-truth repository?▼

To fact-check a proposal draft, this Skill extracts explicit and implicit claims like numbers and dates, then cross-references them against a centralized DataStore repository to grade accuracy and flag inconsistencies. You receive a comprehensive forensic risk report for manual review.

What is forensic claim extraction for content validation?▼

Forensic claim extraction is the automated identification of explicit and implicit claims within professional documents, including numbers, dates, and superlatives. This process enables hierarchical validation by grading extracted claims against authoritative source documents as Validated, Unverified, or Contradicted.

Can I use automated fact-checking for investor-facing financial documents?▼

Yes, automated fact-checking is designed for high-stakes professional content like investor-facing documents. The Skill performs risk assessment by assigning risk levels to unverified claims, prioritizing manual review to prevent financial or legal discrepancies in your drafts.

What's the best way to verify data integrity in professional decks and letters?▼

The best way to verify data integrity is running a comparative analysis against authoritative reference documentation. This Skill cross-references your decks and letters against a verified DataStore index, ensuring strict consistency and eliminating factual errors.

Do I need a DataStore index to perform risk-based content audits?▼

Yes, you need access to a centralized DataStore index and reference documentation to perform risk-based content audits. The Skill requires this verified source-of-truth repository to execute comparative analysis and generate accurate risk-based reporting for your drafts.

How does hierarchical validation grade unverified claims?▼

Hierarchical validation grades unverified claims by comparing them against a strict source-of-truth hierarchy within the DataStore. It assigns specific risk levels to unverified statements, allowing you to prioritize manual review for high-risk financial or legal content.