Skill UI

A comprehensive security auditing tool designed to detect UEFI Secure Boot bypasses and advanced bootkits (like BlackLotus and Bootkitty). It verifies the Secure Boot state, checks the freshness of the dbx revocation list, and hashes EFI boot binaries against known-bad sets. Use this skill for auditing enterprise fleets after major bootkit advisories or for hunting pre-OS persistence on compromised endpoints.

A systematic skill designed to investigate data incidents, including freshness delays, volume anomalies, schema changes, and ETL failures. It guides the agent through a comprehensive process using Monte Carlo's observability metadata and optional direct data querying to pinpoint the root cause.

This skill integrates with Monte Carlo's observability platform to provide a comprehensive health report for data assets. It checks critical metrics including data freshness, active alerts, monitoring coverage, asset importance, and the health of upstream dependencies. Activates when users inquire about the status, reliability, or quality of a data table.

This skill helps optimize and verify latency-sensitive systems such as real-time dashboards, market data feeds, and streaming agents. It involves tracking p50/p95/p99 latency, freshness age, and queue depth. You will map hot paths and run live readbacks to ensure performance. Use this when throughput or data freshness matters in engineering contexts.

This comprehensive guide provides expert strategies for structuring and auditing the "Related Work" section for top-tier NLP conferences (like ACL). It covers citation hygiene (Anthology vs. arXiv), maintaining temporal freshness against rapidly evolving baselines, and articulating clear technical contrasts to prove the novelty of your research. Essential for high-stakes academic publishing.

A comprehensive guide for authors submitting papers to web conferences. It details how to structure empirical claims, ensuring evidence matches the claim's scope (scale, freshness, generalizability). The guide covers avoiding methodological flaws like temporal or popularity leakage, selecting datasets with proper provenance, and performing rigorous ablations and statistical analysis for maximum academic rigor.

This skill handles the deployment of a Dataverse solution zip file into a target environment. It supports standard imports and advanced staged imports for dependency validation before committing changes. Crucially, it incorporates a robust ALM plan gate to ensure proper deployment strategy execution, checking for plan existence and data freshness.

A powerful tool for deterministic and reproducible retrieval of evidence from specialized academic and policy corpora. It supports searching arXiv (preprints), PubMed/PMC (biomedical literature), and US policy documents. Users can check corpus freshness, retrieve stable metadata, and fetch full-document Markdown for high-reliability research tasks.

This skill investigates data incidents like freshness delays, volume anomalies, and ETL failures using Monte Carlo MCP tools. It combines observability metadata with optional direct data querying to identify root causes systematically.

This skill evaluates the health of data assets using Monte Carlo's observability platform. It generates structured reports on freshness, alerts, monitoring coverage, importance, and upstream dependencies. Use it when users inquire about asset status, reliability, or quality.

This skill identifies outdated elements in content such as statistics, dates, and examples to maintain freshness. It helps optimize SEO by suggesting updates, prioritizing pages based on ranking decay, and providing actionable refresh plans including new sections and verified data. Use it for older content needing revitalization.