realitycheck-stats

Count claims, sources, chains, and predictions from the Reality Check database.

38|Updated Jan 20, 2026

Search Tags:#database #reporting #sources #stats #claims #audits

Ready to run

npx skills add https://github.com/lhl/realitycheck --skill realitycheck-stats

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: realitycheck-stats
Source: https://github.com/lhl/realitycheck/tree/main/integrations/amp/skills/realitycheck-stats
Command: npx skills add https://github.com/lhl/realitycheck --skill realitycheck-stats

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a concise, on-demand summary of the Reality Check knowledge base by counting claims, sources, chains, and predictions to reveal coverage and gaps.

Core Features & Use Cases

Live overview: Retrieve counts for claims, sources, chains, and predictions to assess knowledge base size.
Breakdown insights: See distributions by domain, type, and evidence level to guide data quality audits.
Use Case: During a data governance review, generate a snapshot of current statistics for reporting and planning.

Quick Start

Run the database stats command: rc-db stats or: uv run python scripts/db.py stats

Frequently Asked Questions about realitycheck-stats

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

FAQPage Schema

How do I get live database stats for claims, sources, and predictions?▼

To retrieve live database stats for claims, sources, and predictions, run the rc-db stats command or execute the Python database script to query the live data store and return structured counts for an instant knowledge base overview.

What is included in the database stats breakdown for data governance audits?▼

The database stats breakdown for data governance audits includes structured counts of claims, sources, chains, and predictions, alongside distributions by domain, type, and evidence level to reveal coverage gaps and guide quality assurance reviews.

Can I use a Python script to generate reporting snapshots for data quality assurance?▼

Yes, you can use a Python script to generate reporting snapshots for data quality assurance by running uv run python scripts/db.py stats, which queries the live data store and returns structured counts and breakdowns for auditing workflows.

Do I need any external dependencies to run database health checks and overview analyses?▼

No external dependencies are required to run database health checks and overview analyses, as the skill operates independently to query the live data store and return structured counts for claims, sources, chains, and predictions.

When do I need to retrieve database stats during a data governance review?▼

You need to retrieve database stats during a data governance review when you require an on-demand snapshot of current statistics for reporting and planning, enabling quick health checks and audits to assess knowledge base size and coverage.