Investigating Anomalous Results

When something breaks or looks wrong, the natural instinct is to tweak until it passes. This skill enforces the opposite: find the root cause before changing anything. It walks through four phases, from characterizing the anomaly and instrumenting each pipeline stage to forming testable hypotheses and documenting the actual resolution. The iron law is simple: no dropping data, changing parameters, or rerunning with different seeds until you know whether it's a code bug, data issue, or real finding. Honestly, this is most useful when the anomaly is convenient and supports what you wanted to see, because that's when the temptation to skip investigation is strongest. It's structured enough to follow under pressure when your judgment is weakest.

Install to Claude Code

npx -y skills add k-dense-ai/science-superpowers --skill investigating-anomalous-results --agent claude-code