Skill UI

A comprehensive runbook designed for on-call engineers to manage Databricks incidents, outages, and major job failures. It provides structured procedures for immediate triage, decision tree guidance (covering cluster failures, code errors, and data quality issues), and steps for evidence collection and postmortem documentation, ensuring rapid and systematic incident resolution.

A comprehensive workflow for systematically reviewing medical evidence. It allows users to search databases for clinical studies, build curated citation collections, grade evidence using established frameworks like GRADE, and generate professionally formatted, structured reports in academic citation styles (e.g., AMA). Ideal for conducting literature reviews and supporting clinical research. This tool helps transform raw medical data into actionable, structured knowledge.

This guide outlines a systematic methodology for gathering, reading, and synthesizing large bodies of academic research for comprehensive economic surveys (JEL style). It moves beyond simple summarization by enforcing structured data collection into a detailed evidence matrix. The process ensures maximum coverage through advanced search techniques (e.g., snowballing, JEL code sweeps) and focuses on synthesizing connections, identifying consensus, and articulating scholarly tensions across different studies.

This guide provides methodological standards for defending the empirical design of a language manuscript. It covers various subfields—including fieldwork, corpus construction, phonetics, and typological comparison—ensuring that the evidence base is transparent, rigorous, and directly supports the stated theoretical claims. Use this when justifying data collection methods or addressing reviewer concerns about evidence validity.

This skill guides authors on positioning information retrieval (IR) work for the Text REtrieval Conference (TREC). It functions as a venue-selection and manuscript re-framing tool, ensuring the submission aligns with TREC's focus on shared evaluation tracks, test collections, and NIST-style benchmarking. It helps authors structure evidence, understand reviewer expectations, and distinguish the work from general CS conference submissions.

A specialized skill for conducting authorized Open Source Intelligence (OSINT) and cyber threat intelligence gathering. It enriches Indicators of Compromise (IOCs), tracks malicious campaigns, and analyzes impersonation or scamming narratives from public platforms like X/Twitter. The process mandates rigorous evidence corroboration, source preservation, and structured handoff to digital forensics or threat-hunting pipelines.