ds-using-superpowers

Analytics notebook requests are routed to the correct data science workflow by evaluating the task context against a routing table and priority rules, then invoking the matching local ds-skill instructions before any analysis begins.

The best way to prevent premature SQL execution is to route experiment planning and A/B test design requests through a priority-driven workflow that enforces metric validation and systematic debugging guardrails before any queries run.

Systematic debugging for vague research questions works by matching the query context to a specific local ds-skill using deterministic routing, which then enforces checklist-first execution and multi-step planning to resolve the ambiguity.

Yes, the routing approach supports Vertica and Spark execution paths by evaluating the analytics request context and dispatching it to the appropriate local ds-skill workflow with reproducibility and readability guardrails applied.

Pre-completion verification for metric definition risks is needed whenever an analytics request involves metric validation, ensuring the assistant follows checklist-driven tasks from the invoked skill before finalizing any analytical response.

Yes, it requires reading and invoking matching local ds-skill instructions stored in the `.codex/skills` directory, using the routing table and skill priority rules to enforce deterministic workflow selection.