Skill UI

A comprehensive, expert-level workflow for debugging complex software issues in production environments. This skill guides users through initial triage, advanced observability data collection (APM, distributed traces, logs), intelligent hypothesis generation, and full root cause analysis. Use it when dealing with intermittent failures, performance bottlenecks, or needing a complete fix and prevention plan.

Hypogenic automates LLM-driven hypothesis generation and testing over tabular datasets, blending literature insights with empirical analysis to accelerate discovery in domains like deception detection or AI content evaluation.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

This technique is designed for entity recognition and hypothesis generation when identifying Indian or Bollywood actors based on indirect clues. Instead of running broad searches, users should hypothesize a small set of candidate names (1-3) using the provided clues (e.g., awards, family history, controversies). Subsequently, targeted verification searches must be executed for each constraint against the candidate names to confirm the correct identity.

Hypogenic automates LLM-driven hypothesis generation and testing over tabular datasets, blending literature insights with empirical analysis to accelerate discovery in domains like deception detection or AI content evaluation.

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.