Come usare
- Copia il comando e controlla il pacchetto prima di installarlo nel tuo ambiente agente.
- Controlla strumenti, credenziali e ambienti richiesti nel documento originale.
- Descrivi input e risultato desiderato; confronta l’output con le fonti.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill design-falsification-testPrima di iniziare
- L’installazione non include abbonamenti, quote API o accesso ai file.
- Stelle e installazioni indicano attività, non un test indipendente di qualità o sicurezza.
Documento Skill originale
Contenuto dal repository con titoli, esempi, codice, tabelle, link e immagini preservati.
design-falsification-test
Purpose
Specify a concrete observation, computation, intervention, counterexample, or measurement that could count against a claim.
Input contract
yaml
required: [sharp_claim, scope, candidate_observables]
optional: [cost, available_tools, competing_predictions]
constraints: [test must identify a failure condition and measurement rule]Procedure
- Enumerate claim commitments and possible failure observations.
- Rank tests by information value and cost.
- Specify the cheapest decisive test with pass/fail interpretation.
If the falsification test has an executable intervention and verdict rule, consider execute-probe as the next tactic.
Output contract
yaml
produces: [falsification_test, failure_condition, measurement_plan, priority_rationale]
delta_fields: [findings, evidence_updates, uncertainties, decisions]Quality gates
- Test must be capable of producing evidence against the claim, not only confirming examples.
Failure and counterexamples
Do not design a test whose acceptance criterion is copied from the claim.
Provenance map
- resolved: red-team-truthseeking
