---
name: information-verification
description: "Verify important information by tracing provenance, counting independent sources instead of repetitions, preserving corrections and keeping verified, disputed and unknown claims separate."
---

# Information Verification

Verify important information by tracing provenance, counting independent sources instead of repetitions, preserving corrections and keeping verified, disputed and unknown claims separate.

## When to use

- A claim feels true mainly because it is familiar or repeated.
- Several articles or summaries may depend on the same original source.
- A correction exists but the older explanation still shapes discussion.
- A generated answer makes consequential claims without inspectable provenance.

## Workflow

1. Extract the consequential claims instead of trying to verify the whole document at once.
2. For each claim, trace the earliest reliable or primary source you can actually inspect when tools are available.
3. Map source lineage and count independent evidence streams, not links or repetitions.
4. Look for corrections, later updates, contradictory evidence and date/version mismatches.
5. Restate the currently supported replacement explanation when an earlier claim was corrected.
6. Return a claim ledger with verified, supported-but-limited, disputed, unverified or unknown status and the reason for each label.

## Required output

- Claim ledger
- Provenance / source lineage
- Independent confirmation count where knowable
- Corrections and version/date notes
- Open verification gaps
- What is safe to rely on now

## Evidence and safety boundaries

- Do not call a claim verified when you cannot inspect supporting evidence.
- Do not treat multiple summaries of one source as independent confirmation.
- Do not erase the correction history when a claim changes.
- Do not infer truth from popularity, repetition or confident language.
## Evidence-linked lenses

Use these as candidate lenses, not diagnoses:

- [Illusory Truth Effect](https://cognitive-biases.github.io/biases/truth-judgment-illusory-truth-effect/) — Repeated claims receive higher truth ratings than comparable new claims on average, but the effect is heterogeneous and does not generalize equally to every kind of statement. A 2026 systematic review and meta-analysis covering 182 studies, 366 effect sizes and more than 31,000 participants found a reliable corrected average effect. A later 2026 paper with two preregistered experiments found little or no meaningful repetition effect for social-political opinion statements. The useful claim is therefore narrower than 'repeat anything and people will believe it.'
- [Continued Influence Effect](https://cognitive-biases.github.io/biases/memory-bias-continued-influence-effect/) — The continued influence effect describes a specific pattern: false or outdated information can keep affecting later reasoning even after a clear correction. It does not mean the correction had no effect, that the person rejected the correction, or that belief in the false claim became stronger. Corrections often reduce misinformation reliance without removing it completely. That distinction matters because continued influence is much broader than the rarer backfire outcome.
- [Confirmation Bias](https://cognitive-biases.github.io/biases/cognitive-bias-confirmation-bias/) — Confirmation bias is an umbrella label for several ways existing beliefs or hypotheses can influence information search and interpretation. It should not be reduced to one behaviour such as reading only agreeable news, and a preference for confirming tests is not irrational in every task or environment.
- [Availability Heuristic](https://cognitive-biases.github.io/biases/heuristic-bias-availability-bias/) — Availability is a judgment heuristic: people can use how easily examples or scenarios come to mind when estimating frequency or probability. That shortcut is not automatically an error because memorable or accessible examples can correlate with real frequency. Bias appears when accessibility is driven by factors that are not diagnostic of the quantity being judged.

## References

- [Decision skill](https://cognitive-biases.github.io/skills/information-verification/)
- [Checking claims context](https://cognitive-biases.github.io/contexts/checking-claims-misinformation/)

## Portability

This is an instruction-only Agent Skill. It requires no secrets, no executable scripts and no network access to run. If source-access tools are available, use the linked Cognitive Biases material to preserve review state and uncertainty.

Licence: CC BY-NC-SA 4.0. Commercial reuse requires prior written permission.