Falsify

Falsify

Take a claim and apply Popperian falsification: is the claim falsifiable, what evidence would disprove it, and does the existing evidence actually support it — or does it merely fail to contradict it? The distinction matters. A claim that cannot be proven wrong is not a strong claim; it is an unfalsifiable one.

Use this when a decision is being justified by evidence that has not been scrutinized, or when something "seems supported" but the reasoning has never been stress-tested.

Behavior Constraints

<output_contract>

Present the falsification analysis as:

• Claim — the claim restated precisely and completely
• Falsifiability — is the claim falsifiable? If yes, state what a disconfirming observation would look like. If no, explain why and flag it as unfalsifiable.
• Disconfirming evidence — what specific evidence, if observed, would weaken or disprove the claim. Be concrete: not "evidence against X" but "if Y were measured and found to be Z."
• Evidence audit — assess the evidence currently cited in support of the claim:
  • Does it actually support the claim, or does it only fail to contradict it?
  • Is it subject to selection bias, confounding, or base rate neglect?
  • What is the quality and source of the evidence?
• Verdict — one of: well-supported, weakly supported, unsupported, or unfalsifiable — with a one-sentence justification

</output_contract>

<completeness_contract>

The task is complete when the evidence audit goes beyond surface-level review — it must distinguish between "this evidence supports the claim" and "no evidence contradicts the claim." If the claim is genuinely well-supported and the evidence holds up to scrutiny, say so.

</completeness_contract>

<reasoning_rules>

• Absence of evidence is not evidence of absence, but it is also not confirmation. Flag when a claim is being treated as supported simply because it has not been challenged.
• Do not conflate this with think-devils-advocate. Devils-advocate challenges the position. Falsify challenges the evidence supporting it.
• Unfalsifiable claims are not necessarily wrong — but they are not scientific claims and should not be treated as empirical justification for decisions.
• Be precise about what the evidence actually shows. "Studies suggest X" is not the same as "X has been demonstrated under conditions Y and Z."

</reasoning_rules>

Workflow

1. Ask the user for the claim and any supporting evidence if not already provided. Optionally ask:
   • What decision this claim is being used to justify
   • Where the evidence comes from
2. Assess falsifiability.
3. Audit the evidence and present the output per the output contract above.