Verify Claims

Fact-Checking Skill

Verify claims and information using professional fact-checking services from around the world.

Core Principles

1. Multiple sources - Cross-reference findings from several fact-checking organizations
2. Regional relevance - Prioritize fact-checkers appropriate to the content's context
3. Language matching - Use fact-checkers in the native language of the content when possible
4. Credible sources only - Never use fraudulent or unreliable fact-checking services
5. Balanced presentation - Present both confirming and contradicting findings fairly

When to Use This Skill

Trigger this skill when the user:

• Explicitly asks to fact-check, verify, or validate information
• Shares an article, video transcript, or claim and asks "is this true?"
• Wants to check if something is misinformation or a hoax
• Asks about the credibility of specific claims or statements
• Requests verification of news, social media posts, or viral content
• Wants to cross-reference information with trusted sources

Do NOT trigger for:

• General research or information gathering (use web search instead)
• Checking grammar, spelling, or writing quality
• Verifying code functionality or technical documentation
• Questions about opinions rather than factual claims

Workflow

Step 1: Understand the Content

Before beginning verification, analyze what needs to be checked:

1. Identify specific claims - Extract concrete, verifiable statements from the content
2. Note the context - Identify:
   • Geographic references (countries, regions, cities)
   • Named individuals (politicians, public figures, organizations)
   • Languages used in the content
   • Time period or dates mentioned
   • Subject matter (politics, health, science, etc.)
3. Determine user context:
   • User's native language (for selecting appropriate fact-checkers)
   • User's location if relevant

Example Analysis:

• Content: "Video claiming vaccines cause autism, mentions Andrew Wakefield, references UK study"
• Claims to verify: Vaccine-autism link, Wakefield's research
• Context: Medical/health topic, UK origin, English language
• Key entities: Andrew Wakefield, MMR vaccine, UK medical establishment

Step 2: Select Fact-Checking Services

CRITICAL: Begin by fetching the current list of fact-checking services:

Fetch: https://en.wikipedia.org/wiki/List_of_fact-checking_websites

From this list, select 3-7 relevant fact-checking services based on:

Selection Criteria

1. User's language/location - Always include fact-checkers in the user's native language

2. Content language/location - If different from user's language, also include fact-checkers in the content's language and region

3. Geographic relevance - If content mentions specific countries/regions:

   • Include fact-checkers from those countries
   • Example: Content about French politics → include French fact-checkers

4. Subject matter specialists - Some fact-checkers specialize:

   • Health/medical claims → Health Feedback, Science Feedback
   • Politics → country-specific political fact-checkers
   • General → Snopes, FactCheck.org, Full Fact

5. Person-specific - If content focuses on specific public figures:

   • Include fact-checkers from their home countries
   • Example: Claims about a US politician → include US fact-checkers

Exclusion Rule

NEVER use services listed under "Fraudulent fact-checking websites" on the Wikipedia page, regardless of how well they match other criteria.

Prioritization

When you must limit selections:

• Prioritize: User's language > Content's language > Geographic relevance
• Prefer well-established services (FactCheck.org, Snopes, Full Fact, AFP Fact Check, etc.)
• Include at least one international/general service

Example Selection:

• User: Polish speaker
• Content: English article about US vaccines
• Selected services:
  1. Demagog.pl (Polish, for user)
  2. FactCheck.org (US, for content geography)
  3. Snopes (US, general/medical)
  4. Health Feedback (health specialist)
  5. Full Fact (UK, English-speaking, general)

Step 3: Search Each Fact-Checking Service

For each selected service, conduct targeted searches:

Search Strategy

1. Extract 2-4 search terms from the content:

   • Key person names
   • Main topics/subjects
   • Specific claims or events
   • Important keywords

2. Translate terms to the fact-checker's native language if needed

3. Construct search queries using DuckDuckGo with site operator:

   Format: site:domain.com [search terms in appropriate language]
   
   Examples:
   - site:fullfact.org vaccines autism
   - site:demagog.org.pl szczepionki autyzm
   - site:factcheck.org Andrew Wakefield MMR
   - site:healthfeedback.org vaccine safety

4. Execute 1-3 searches per fact-checker (depending on content complexity)

Search Best Practices

• Keep queries concise (2-4 words typically)
• Start broad, then narrow if needed
• Don't repeat very similar queries
• If first search yields good results, proceed to analysis
• If first search yields poor results, try alternative terms

Step 4: Analyze Search Results

For each fact-checking service:

1. Review search results - Examine the first 5-10 results from each search

2. Select relevant articles - Choose articles where:

   • Headline directly addresses the claim being verified
   • Content appears substantial (not just brief mentions)
   • Publication date is relevant (recent for ongoing issues, any date for historical debunks)

3. Fetch and read articles - Use web_fetch to retrieve the full text of 2-4 most relevant articles per fact-checker

4. Extract key findings for each article:

   • Verdict - What did the fact-checker conclude? (True, False, Misleading, Mixed, Unproven, etc.)
   • Evidence - What evidence did they cite?
   • Context - Any important nuance or context
   • Relevance - How directly does this address the user's claim?

Step 5: Synthesize and Present Results

Organize findings into a clear, user-friendly format:

Handle Fresh Content First

Before presenting results, check if the content is very recent (3 days old or less):

1. If fact-checks found: Proceed normally with presentation

2. If no fact-checks found AND content is ≤3 days old:

   • Note that the content is too fresh for fact-checkers to have covered it yet
   • If task scheduling is available:
     • Schedule a follow-up fact-check for 3 days from now
     • Inform user: "I've scheduled a follow-up check for [date]. I'll notify you if fact-checkers have published verification by then."
   • If task scheduling is NOT available:
     • Suggest: "This content is very recent (published [date]). Fact-checkers typically need a few days to verify claims. I recommend checking back in 3 days for updated verification."
   • Offer preliminary analysis using general web search
   • Proceed with any available information from general sources

3. If no fact-checks found AND content is older:

   • Note that fact-checkers haven't specifically covered this
   • Offer general web research instead

Structure Your Response

1. Opening summary (2-3 sentences)

   • Overall consensus from fact-checkers
   • Brief answer to the user's question

2. Key findings by claim (if multiple claims)

   • Group related findings together
   • Present contradicting evidence if it exists

3. Detailed evidence (organized by fact-checker or by claim)

   • Include specific verdicts
   • Cite evidence fact-checkers used
   • Note any disagreements between fact-checkers

4. Important context (if relevant)

   • Historical background
   • Why the claim persists
   • Common misconceptions

5. Source citations

   • Provide direct links to all fact-checking articles referenced
   • Format: [Fact-Checker Name]: Article Title (Date if available) - [URL]

Presentation Guidelines

• Be objective - Present findings without inserting personal judgment
• Be nuanced - Avoid oversimplifying complex issues
• Be clear about uncertainty - If fact-checkers disagree or evidence is inconclusive, say so
• Be balanced - If some evidence supports and some contradicts, present both
• Use accessible language - Avoid jargon, explain technical terms
• Highlight consensus - When multiple fact-checkers agree, emphasize this

Formatting

• Use clear headers to organize different claims or themes
• Use natural prose, not bullet points, for the main findings
• Only use lists for: multiple similar items, source citations, or when explicitly helpful
• Include clickable citations throughout (not just at the end)

Example Response Structure

Based on verification from five established fact-checking organizations, the claim that vaccines cause autism has been thoroughly debunked. Multiple independent reviews of the evidence have found no causal link between vaccination and autism spectrum disorder.

The origins of this claim trace back to a fraudulent 1998 study by Andrew Wakefield, which was later retracted by The Lancet. Fact-checkers consistently note that Wakefield lost his medical license, and subsequent large-scale studies involving millions of children have found no connection.

[Full Fact reviewed the evidence in 2023](link), concluding "There is no link between the MMR vaccine and autism." Their analysis examined 12 major studies and found consistent results across different populations and methodologies.

[FactCheck.org's comprehensive analysis](link) explains that "The myth persists despite overwhelming scientific consensus against it" and details how the original study was not only retracted but shown to involve falsified data.

However, [Demagog.pl](link) notes that while the vaccine-autism link is false, concerns about vaccine safety in general are legitimate and should be addressed through proper scientific channels rather than dismissed.

**Important context**: The persistence of this myth has real public health consequences, as fact-checkers note declining vaccination rates in some communities. Understanding why the claim was debunked helps address ongoing concerns.

**Sources consulted:**
- Full Fact: "MMR vaccine does not cause autism" - [link]
- FactCheck.org: "Wakefield's Fraudulent Research" - [link]  
- Snopes: "Vaccines and Autism" - [link]
- Demagog.pl: "Szczepionki i autyzm - mit czy prawda?" - [link]
- Health Feedback: "Scientific consensus on vaccine safety" - [link]

Common Scenarios

Scenario 1: Single Specific Claim

User request: "Is it true that 5G causes COVID-19?"

Approach:

• Identify claim: 5G technology causes or spreads COVID-19
• Select 4-5 general fact-checkers (international scope, tech/health focus)
• Search for "5G COVID" or "5G coronavirus"
• Expected result: Multiple fact-checkers will have debunked this
• Present: Clear consensus with explanation of why the claim is false

Scenario 2: Article with Multiple Claims

User request: "Can you fact-check this article about climate change?"

Approach:

• Extract 3-5 specific verifiable claims from the article
• Select fact-checkers: user's language + climate-focused services
• Search each claim separately
• Present: Findings organized by claim, with overall assessment

Scenario 3: Complex Political Claim

User request: "Did [politician] really say/do [thing]?"

Approach:

• Identify the specific claim and context
• Select fact-checkers from politician's country + user's language
• Search politician's name + key terms
• Present: Direct answer with context, including if statement was taken out of context

Scenario 4: Viral Social Media Content

User request: "I saw this video on TikTok claiming [X], is it real?"

Approach:

• Identify what's being claimed in the video
• Select broad, well-known fact-checkers (viral content often fact-checked widely)
• Search for key terms from the claim
• Present: Whether it's been debunked, original context if misrepresented