Skill UI

This skill guides the systematic process of conducting comprehensive academic literature reviews. It allows users to search multiple biomedical, scientific, and technical databases (e.g., PubMed, arXiv, Semantic Scholar) to synthesize current knowledge. The output generates professionally formatted reports (Markdown/PDF) with verified citations, and mandatorily integrates AI-generated scientific schematics to enhance visualization and depth, suitable for research papers, meta-analyses, and state-of-the-art reports.

This guide provides comprehensive technical instructions for optimizing Palantir Foundry costs. Learn to use incremental transforms to drastically reduce compute rebuilds, right-size Spark profiles based on data volume, and migrate from expensive API polling to efficient, event-driven webhooks, ensuring both cost efficiency and system stability.

A comprehensive guide to diagnosing and enhancing search relevance within Qdrant. This skill addresses reported issues such as low precision, low recall, or irrelevant matches. It guides users through determining if the problem lies in the embedding model, Qdrant configuration, or the query strategy. Techniques covered include optimizing chunk splitting, tuning HNSW parameters, implementing hybrid search, and utilizing reranking for superior result quality.

This guide covers advanced retrieval strategies that significantly boost search quality beyond basic vector similarity search. Techniques include Hybrid Search (combining dense and sparse indexing), Reranking (improving result order), Relevance Feedback (guiding search with iterative user scores), and Maximal Marginal Relevance (MMR) for diversity. Use these methods when standard search results lack relevance, miss critical keywords, or exhibit poor precision.

This advanced skill is an end-to-end tool for transforming complex research topics into professional, visualized knowledge graph PDFs. It automatically conducts multi-round web searches, extracts key entities, structures related knowledge, and designs the optimal visualization (supporting Graphviz, PlantUML, etc.). Ideal for deep academic analysis, mapping character relationships, or visualizing complex technical architectures where existing structured data is unavailable.

A comprehensive guide for deep debugging complex Snowflake issues. This guide covers advanced techniques including detailed query profiling (spill analysis), diagnosing lock contention and transaction conflicts, analyzing metadata operations, and optimizing partition usage. Use it when standard troubleshooting fails to address slow queries or warehouse performance bottlenecks.

A comprehensive guide detailing the process of migrating data warehouses to Snowflake from major sources like Amazon Redshift, Google BigQuery, or on-premise databases. This resource covers critical steps including schema conversion (handling dialect differences like STRUCT/ARRAY to VARIANT), robust data transfer methods (S3/Cloud Storage, Python/Pandas), data validation techniques (checksums, row counts), and essential SQL syntax translation patterns.

A comprehensive guide to implementing production-grade reliability patterns for Snowflake environments. Covers advanced techniques like Time Travel for point-in-time recovery, cross-region database replication, account failover groups for disaster recovery, and application-level resilience coding (e.g., connection failover logic). Essential for building fault-tolerant, highly available data pipelines.

A comprehensive playbook for digital forensic experts. It details systematic techniques and tools for detecting and extracting hidden data embedded across various media types, including images (LSB, PNG chunks, JPEG DCT, EXIF metadata), audio (spectrogram, DTMF), and files (polyglots, appended data). Essential for deep-dive forensic investigations.

A comprehensive, advanced playbook for conducting deep network traffic analysis and PCAP forensics. Covers essential skills like PCAP repair, advanced Wireshark filtering (HTTP, DNS, TLS), data extraction (file carving, credential harvesting), and detecting covert channels. It guides users through sophisticated techniques, including TLS decryption workflows and DNS tunneling identification.

This engine aggregates news from multiple RSS sources (e.g., TechCrunch, The Verge) and performs advanced sentiment analysis using AI (Claude). It ranks articles by industry impact, generates structured summaries, and provides actionable commentary, making it ideal for daily tech/AI briefing preparation and market monitoring.

This skill converts complex, narrative technical documents, research excerpts, or natural language problem descriptions into a highly structured Mathematical Problem Specification (MPS). It systematically extracts variables, constraints, objectives, and uncertainty parameters. By adhering to a strict Zero-Inference Protocol, it ensures all extracted elements are strictly grounded in the source text, making it invaluable for formalizing real-world optimization, data science, and engineering problems.