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falsifiability-check

Research
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SOP: check whether a hypothesis meets the falsifiability criterion

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How to use this skill

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  3. Review the proposed files and risks before you approve installation.
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Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/falsifiability-check/SKILL.md

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Falsifiability Check

Check hypotheses against Popper's falsifiability criterion, ensuring every hypothesis has an explicit refutation condition.

HARD-GATE

Not satisfied → stop and return an error: hypothesis statement is incomplete.

Pipeline

  1. Pre-check: verify the completeness of the hypothesis statement
  2. Observable-prediction derivation: derive ≥2 specific observable predictions from the hypothesis
  3. Refutation-prediction construction: construct "what should be observed if the hypothesis is wrong"
  4. Feasibility assessment: is the refutation prediction testable technically and ethically?
  5. Verdict: falsifiable / not falsifiable / needs revision
  6. If not falsifiable: provide specific revision suggestions to make it falsifiable
  7. Output the verdict

Output Format

{
  "hypothesis_id": "H1",
  "statement": "...",
  "positive_predictions": [
    "If H1 is true, we should observe X in condition Y"
  ],
  "falsification_scenario": "Specific observation that would conclusively refute H1",
  "testability": "high | medium | low",
  "verdict": "falsifiable | not_falsifiable | needs_revision",
  "revision_suggestion": "How to make it falsifiable (null if already falsifiable)",
  "notes": "Additional considerations"
}