What problem does it solve? It prevents false detection-efficacy claims by defining exactly what counts as proof that a TinySocs detection rule works, distinguishing synthetic xUnit tests from live Atomic Red Team attack validation. ## Core Features & Use Cases - Two-mechanism validation model: Explains what xUnit synthetic-event tests (48 executable cases) prove versus what the Atomic Red Team live-attack harness proves, and why neither alone is sufficient. - Numbers discipline: Enforces which efficacy figures are quotable (88.9% curated) versus banned (57.1% raw, March 100%), with curated-vs-raw denominator rules. - Harness scar-tissue documentation: Catalogs deliberate engineering choices in Test-AtomicDetection.ps1 (curl over Invoke-RestMethod, _source projection, day-scoped indices) that must not be cleaned up. - Use Case: When asked "is rule TS-061 validated" or "what does 88.9% mean", consult this Skill to answer honestly using the harness-validated definition and current atomic-results.json state. ## Quick Start Ask the AI to load the tinysocs-validation-and-qa skill and explain whether detection rule TS-070 is validated and what evidence backs that claim.