fact-checker

name

fact-checker

description

Investigate a news article URL for factual accuracy, rhetorical manipulation, and media quality. Extracts claims, gathers independent evidence via web search, assesses each claim, and runs media-quality analyzers (misrepresentation, temporal manipulation, statistical deception, selective quotation, rhetorical fallacies, contextual gaps, emotional manipulation). Use when asked to fact-check, investigate, or analyze a news article URL.

Fact-Checker Investigation

Ported from Frank Investigator — a Rails app that runs a multi-step news fact-checking pipeline. This skill replaces Rails jobs with agent orchestration, Chromium with WebFetch, and DuckDuckGo scraping with WebSearch.

Pipeline Overview

URL → Fetch → Extract Claims → Search Evidence → Assess Claims
  → Content Analysis (5-in-1) → Rhetorical Fallacies
  → Contextual Gaps (+ search) → Emotional Manipulation → Summary

Instructions

When given a news article URL, run the pipeline below in order. Each step feeds the next. Write all analysis output in the article's language.

Present a short progress line before each step so the user sees pipeline movement.

Step 1: Fetch Article

Use WebFetch on the URL. Extract:

• title: the article headline
• host: the domain (e.g. folha.uol.com.br)
• body_text: the article body (strip nav, ads, cookie notices, boilerplate)
• published_at: publication date if visible

If the fetch fails or returns mostly boilerplate, tell the user and stop.

Step 2: Extract Claims

Analyze the article body and extract 3–8 core factual claims.

Follow the claim extraction criteria in analyzers.md § Claim Extraction.

For each claim produce:

• text: the claim as stated
• canonical_form: rewritten as clear Subject-Verb-Object (proper nouns, ISO dates, "X%")
• importance: high / medium / low
• checkability: checkable / not_checkable / ambiguous

Discard opinions, rhetoric, background filler, vague statements, and duplicates. Fewer precise claims are better than many vague ones.

Step 3: Gather Evidence

For each checkable claim:

1. Generate 2–3 concise search queries (under 10 words each, in the article's language, excluding the original outlet name).
2. Run WebSearch for each query.
3. For the top 2–3 results per claim, run WebFetch to get the article content.

Collect evidence as: { url, title, excerpt (first ~500 chars of body) }.

Step 4: Assess Claims

For each claim + its evidence, determine:

Field	Values
verdict	supported, disputed, mixed, needs_more_evidence, not_checkable
confidence	0.0 – 0.97
reason_summary	Must cite specific evidence sources by URL or title

Follow the assessment rules in analyzers.md § Claim Assessment.

Be conservative: prefer needs_more_evidence over a weak supported or disputed.

Step 5: Batch Content Analysis (5-in-1)

Analyze the full article for these five dimensions in a single pass. Follow the detailed criteria in analyzers.md § Batch Content Analysis.

1. Source Misrepresentation — does the article accurately represent its cited sources?
2. Temporal Manipulation — is old data presented as current?
3. Statistical Deception — are numbers presented misleadingly?
4. Selective Quotation — are quotes taken out of context?
5. Authority Laundering — does the citation chain inflate low-authority sources?

Calibration: not every article has problems. Return empty findings and high integrity scores when no issues exist. Minor editorial choices are NOT deception.

Step 6: Rhetorical Fallacy Analysis

Detect logical fallacies from this set: bait_and_pivot, appeal_to_authority, false_cause, strawman, anecdote_over_data, loaded_language, false_dilemma, slippery_slope, ad_hominem, cherry_picking, equivocation, odious_categorization, twisted_conclusion, paradox_framing, false_admission, faulty_proof_exploitation.

See analyzers.md § Rhetorical Fallacies for definitions.

Only flag clear, identifiable fallacies. Normal journalistic framing is not a fallacy.

Step 7: Contextual Gap Analysis

Identify what the article doesn't say — the omissions that let factually correct claims assemble into a misleading narrative. Look for the 9 omission patterns listed in analyzers.md § Contextual Gaps.

For each gap:

1. State the unaddressed question
2. Explain why it matters
3. Run WebSearch with a targeted query to find counter-evidence
4. Report what you found

Rate overall completeness_score (0.0–1.0): 1.0 = complete, <0.4 = critical context missing.

Step 8: Emotional Manipulation Score

Assess whether emotional appeals substitute for evidence or accompany it.

• High emotion + high evidence = passionate journalism (low manipulation)
• High emotion + low evidence + deception signals = manipulation (high score)

Use all prior analyzer scores as inputs. See analyzers.md § Emotional Manipulation.

Step 9: Executive Summary + Honest Headline

Synthesize all findings into:

1. Overall quality: strong / mixed / weak / insufficient (see rating guide in analyzers.md § Summary)
2. Conclusion: 2–3 sentence executive summary
3. Strengths: bullet list
4. Weaknesses: bullet list
5. Honest headline: what the headline SHOULD have been — more accurate, no sensationalism, no euphemism. If the original is already fair, keep it unchanged.

Output Format

Present the final report in this structure:

# Investigation: [Article Title]
**Source**: [host] | **Date**: [published_at]
**Original headline**: [title]
**Honest headline**: [honest_headline]
**Overall quality**: [strong|mixed|weak|insufficient]

## Executive Summary
[conclusion]

## Claims Assessment
[Table: claim | verdict | confidence | reason]

## Content Analysis
### Source Misrepresentation — Score: [X]
### Temporal Manipulation — Integrity: [X]
### Statistical Deception — Integrity: [X]
### Selective Quotation — Integrity: [X]
### Authority Laundering — Score: [X]

## Rhetorical Fallacies
[List with type, severity, excerpt, explanation]
**Narrative bias score**: [X]

## Contextual Gaps
[Questions + evidence found]
**Completeness score**: [X]

## Emotional Manipulation
**Temperature**: [X] | **Evidence density**: [X] | **Manipulation score**: [X]
**Dominant emotions**: [list]

## Strengths
- ...

## Weaknesses
- ...

Critical Rules

• NO HALLUCINATION: only reference URLs, sources, claims, quotes, and data that are explicitly present in fetched content. Never invent or guess.
• Calibration over punishment: most articles have imperfections. Minor issues should not accumulate into a harsh verdict. The question is "does this article deliberately mislead?" not "is it perfect?"
• Language: write all analysis in the article's language.