Hum Source Criticism Agent Skill

Source Criticism

Overview

Source criticism is a systematic method for evaluating whether information is trustworthy. Originally from historical methodology, it's now essential for navigating an information environment flooded with misinformation, opinion-as-fact, and AI-generated content.

Framework

IRON LAW: No Source Is Automatically Trustworthy

Every source — including academic journals, government data, and news from
reputable outlets — has potential biases, errors, and limitations. Credibility
is assessed, not assumed. "It's from the New York Times / 中央社" is not
sufficient — WHAT are they reporting, based on WHAT evidence, and do other
sources corroborate it?

Source Classification

Primary sources: Direct evidence from the time/event (original documents, raw data, eyewitness accounts, original research, official records)

Secondary sources: Analysis or interpretation of primary sources (textbooks, review articles, news analysis, biographies)

Tertiary sources: Compilations of primary and secondary (encyclopedias, Wikipedia, databases) — starting points, not endpoints

Four Tests of Source Credibility

1. External Criticism — Is the source authentic?

• Who created it? Are they who they claim to be?
• When was it created? Is the date consistent?
• Is it the original or has it been altered?
• Is the publication/platform reputable?

2. Internal Criticism — Is the content reliable?

• Does the author have expertise in this topic?
• What is the author's potential bias or interest?
• Is the evidence cited? Can it be verified?
• Is the reasoning logical? Are conclusions supported by the evidence?

3. Triangulation — Do multiple independent sources agree?

• Check 3+ independent sources (not copies of the same original report)
• "Independent" means different authors, different organizations, different methods
• Agreement across independent sources strengthens confidence

4. Currency — Is the information current enough?

• When was it published? Has the situation changed since then?
• For fast-moving topics (AI, policy, markets), even 6-month-old sources may be outdated

Red Flags for Misinformation

| Red Flag | Description |

|----------|-----------|

| No author or organization identified | Who stands behind this claim? |

| Emotional language without evidence | Designed to provoke, not inform |

| No primary sources cited | Claims without traceable evidence |

| "Studies show" without naming the study | Vague appeals to authority |

| Single source amplified across many sites | Same claim copied, not independently verified |

| Too good to be true / too outrageous | Extreme claims require extreme evidence |

| URL/domain mimics reputable source | Fakecnn.com, bbc-news.co (not bbc.co.uk) |

Output Format

# Source Evaluation: {Source/Claim}

## Source Identity
- Author/Organization: {who}
- Publication: {where}
- Date: {when}
- Type: Primary / Secondary / Tertiary

## Credibility Assessment
| Test | Assessment | Evidence |
|------|-----------|---------|
| External (authentic?) | ✓/⚠/✗ | {reasoning} |
| Internal (reliable?) | ✓/⚠/✗ | {reasoning} |
| Triangulation (corroborated?) | ✓/⚠/✗ | {other sources checked} |
| Currency (current?) | ✓/⚠/✗ | {relevance of date} |

## Red Flags
- {any detected red flags}

## Verdict
- Credibility: High / Moderate / Low
- Recommended action: {trust / verify further / discard}

Examples

Correct Application

Scenario: Evaluating a viral social media post claiming "Taiwan's GDP will surpass South Korea's by 2027"

| Test | Assessment | Evidence |

|------|-----------|---------|

| External | ⚠ | Anonymous account, no institutional affiliation, chart has no data source |

| Internal | ✗ | Uses nominal GDP (not PPP), cherry-picks semiconductor sector projection, ignores exchange rate volatility |

| Triangulation | ✗ | IMF and World Bank projections show no such convergence; no reputable analyst makes this claim |

| Currency | ✓ | Posted this month |

Red flags: Emotional headline ("Taiwan DESTROYS Korea"), no primary data source cited, single unsourced chart

Verdict: Low credibility — discard ✓

Incorrect Application

• "This is from Reuters, so it must be true" → Credibility assumed, not assessed. Even reputable sources can be wrong, outdated, or framing an issue in a particular way. Violates Iron Law.

Gotchas

• Bias ≠ unreliable: Every source has a perspective. A labor union's report on working conditions is biased but may contain accurate data. Assess bias AND accuracy separately.
• Wikipedia is a starting point: It's a tertiary source with references. Follow the references to primary/secondary sources. Don't cite Wikipedia as evidence — cite what Wikipedia cites.
• AI-generated content: AI can produce convincing but fabricated "sources" (fake papers, fake quotes, fake statistics). Verify that cited sources actually exist.
• Consensus ≠ truth, but it's a strong signal: Scientific consensus (climate change, vaccine safety) is the strongest available evidence. Lone dissenting "experts" who contradict consensus need extraordinary evidence.
• Source credibility is domain-specific: A cardiologist is a credible source on heart disease but not on economics. Match expertise to the claim.

References

• For CRAAP test (Currency, Relevance, Authority, Accuracy, Purpose), see references/craap-test.md
• For fact-checking tools and databases, see references/fact-check-tools.md