fact-checking

Validates claims and deliverables using counter-hypothesis testing with structured verdict reports.

2|Updated Jul 24, 2026
One-click install
npx skills add https://github.com/elbruno/ElBruno.MagenticUI --skill fact-checking-elbruno
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fact-checking
Source: https://github.com/elbruno/ElBruno.MagenticUI/tree/main/.squad/templates/skills/fact-checking
Command: npx skills add https://github.com/elbruno/ElBruno.MagenticUI --skill fact-checking-elbruno

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Agent-generated claims, references, and deliverables often contain unverified assertions, broken URLs, or exaggerated metrics. This Skill standardizes how reviewers challenge claims, test counter-hypotheses, and report confidence levels so quality assurance output is consistent and evidence-based. ## Core Features & Use Cases - Counter-Hypothesis Methodology: For every claim, generate alternative explanations and test them against available data before accepting it. - Structured Review Template: Produces a standardized fact-check report with a claims table, evidence notes, confidence flags (Verified, Unverified, Contradicted), and a final verdict of PASS, PASS WITH NOTES, or NEEDS REVISION. - Reference Verification: Checks that URLs, package names, API endpoints, and external references actually exist. - Use Case: Before approving an architecture decision, a coordinator spawns a challenger agent to fact-check a claim like "this change saves 75% latency", requiring cited evidence within three investigation cycles. ## Quick Start Ask the agent to fact-check a specific claim or deliverable and require cited evidence for every verdict with a maximum of three investigation cycles.

Frequently Asked Questions about fact-checking

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

FAQPage Schema
How do I fact-check claims made by an AI agent?▼

Fact-check agent claims by generating counter-hypotheses for each assertion and testing them against available data. Verify that URLs, package names, and API endpoints exist, then assign a confidence flag of Verified, Unverified, or Contradicted with cited evidence.

What is counter-hypothesis testing in claim verification?▼

Counter-hypothesis testing asks what evidence supports a claim and what would disprove it, then generates alternative explanations and tests them against data. This prevents accepting claims at face value and surfaces contradictions before approval.

When should a fact-check review be triggered automatically?▼

Trigger a fact-check before any architecture decision or when a claim contains superlatives or percentage thresholds such as "saves 75%", "always", or "never". The coordinator spawns a challenger agent limited to three investigation cycles.

What output format does a structured fact-check report use?▼

The report lists claims verified and issues found, a table mapping each claim to a status flag and evidence, the counter-hypotheses tested, and a final verdict of PASS, PASS WITH NOTES, or NEEDS REVISION.

What are the limitations of automated claim verification?▼

Verification depends on access to external references and APIs, so claims without reachable evidence are marked Unverified rather than confirmed or denied. The process flags a suggested verification method but cannot guarantee correctness for inaccessible sources.