Skill UI

A sophisticated tool for optimizing crypto trades across multiple Decentralized Exchanges (DEXs). It aggregates quotes from major aggregators (like 1inch, Paraswap, and 0x) to find the optimal multi-hop route, calculate split orders for large trades, and assess MEV risk, ensuring minimum slippage and gas costs.

Automates splitting datasets into training, validation, and test subsets by generating and running Python code so you can quickly prepare data for machine learning model training and evaluation.

Provide a comprehensive toolkit for RNA velocity inference in single-cell RNA-seq data, modeling unspliced/spliced kinetics to infer differentiation directions, latent time, and driver genes while complementing Scanpy pipelines.

Use this skill to perform read-only API calls for exploring, previewing, searching, and filtering structured datasets hosted on Hugging Face. It allows users to validate dataset availability, list splits, paginate large datasets, and retrieve comprehensive metadata and statistics, making it ideal for data validation and content extraction workflows.

This guide details how to write advanced correlation searches using Splunk's Search Processing Language (SPL). It covers techniques like threshold-based detection, sequence analysis, and anomaly detection to identify sophisticated security threats (e.g., brute force, data exfiltration, lateral movement) in a Security Operations Center (SOC) environment. Mastery of SPL is essential for closing SIEM detection gaps and ensuring compliance.

This skill provides structured procedures for detecting Golden Ticket attacks, a severe threat involving forging Kerberos Tickets in Active Directory. It analyzes Windows Event ID 4769 for indicators such as RC4 encryption downgrades, abnormal ticket lifetimes, and inconsistencies in TGS/TGT requests. Designed for SOC analysts and threat hunters using SIEM platforms (Splunk/Elastic) to enhance security monitoring coverage against credential theft.

Systematically optimizes Security Information and Event Management (SIEM) detection rules in platforms like Splunk and Elastic. This process involves analyzing historical alert volumes, establishing environmental baselines, creating context-aware whitelists, and statistically adjusting detection thresholds to significantly reduce false positives, improving overall security efficacy.

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 utility displays the precise, real-time token usage and estimated cost savings for the current session. It reads directly from the internal session log, ensuring objective and accurate data without requiring AI computation. Triggered by /caveman-stats, it provides immediate performance metrics to monitor API costs and usage patterns.

This comprehensive guide covers essential operations for handling PDF documents, including text, table, and metadata extraction using libraries like pdfplumber. It details document creation with reportlab, merging/splitting with pypdf/qpdf, and advanced OCR for scanned PDFs. Ideal for automating complex document workflows and structured data ingestion.

This guide provides rigorous methodological standards for conducting mechanism analysis (mediation and moderation) in academic economics research. It strongly cautions against the traditional three-step mediation approach due to identification issues, recommending preferred alternatives like split-channel regression and causal moderation analysis to enhance the robustness of causal claims.

A comprehensive guide for developing scientifically rigorous, APA-formatted tables and figures for quantitative communication research. This skill emphasizes that exhibits must be self-contained, displaying effect sizes and uncertainty (not just significance stars), and following strict reporting standards for maximum clarity for reviewers.