Skill UI

This advanced tool generates publication-ready academic figures and illustrations. It employs a sophisticated, multi-stage iterative workflow involving an AI Planner, Layout Optimizer, Style Verifier, and a dedicated native image generation bridge. The process includes strict visual review and self-correction loops (CVPR/NeurIPS standards) to ensure the highest level of academic polish.

Rowan is a comprehensive, cloud-native platform accessible via a Python API for molecular simulation and medicinal chemistry. It streamlines complex drug discovery workflows, including pKa prediction, conformer searching, molecular docking (single and analogue series), protein-ligand cofolding, and molecular dynamics. It eliminates the need for local HPC/GPU infrastructure, making programmatic batch screening and multi-step chemistry pipelines highly scalable and reliable.

This guide provides a comprehensive method for setting up Snowflake observability. It teaches how to leverage built-in ACCOUNT_USAGE views to monitor critical metrics such as query performance (latency, error rates), credit consumption, and storage growth. Furthermore, it demonstrates how to implement automated alerts for operational issues (e.g., high failure rates, stuck warehouses) and export metrics to external monitoring systems like Grafana or Prometheus.

This skill generates a sophisticated, single-screen consumer dashboard mimicking a high-end lifestyle publication's dating column. It moves beyond simple swiping mechanics to visualize complex social metrics, mutual matches, and connectivity trends using editorial typography and restrained design. Ideal for concepts requiring data-driven storytelling about personal or community relationships.

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.

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.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

A comprehensive skill for creating, editing, and analyzing complex spreadsheets (.xlsx, .csv, etc.). This skill excels in financial modeling, ensuring all calculations are managed via dynamic Excel formulas rather than hardcoded values. It supports data analysis using pandas, rigorous formatting standards, and complex formula integrity checks, making it ideal for financial reporting and data visualization.

A comprehensive, 13-agent pipeline designed for rigorous, academic research on any topic. This tool guides users through the entire research lifecycle, from formulating precise research questions (Socratic mode) and designing methodology blueprints, to systematic literature review, cross-source synthesis, bias assessment, meta-analysis, and compiling final reports using APA 7.0 standards. Ideal for students, academics, and researchers needing deep, verifiable insights.

A specialized intelligence tool for comprehensive patent prior-art and landscape analysis. Unlike generic searches, this skill forces commitment to one of five critical sub-use-cases (Novelty Search, Freedom-to-Operate, Competitive Landscape, etc.) before conducting searches across major patent databases (Google Patents, Espacenet, USPTO). It outputs a detailed, editable report containing claim-aware analysis, risk flags, and strategic recommendations.

The Brain Imaging Data Structure (BIDS) is a community standard defining a consistent file naming convention and directory hierarchy for organizing diverse neuroscientific and biomedical datasets. This skill helps users manage, validate, query, and convert various modalities (MRI, EEG, PET, behavioral, etc.) into a standardized, shareable format, ensuring data integrity for research and publication.

A dedicated skill for performing manual synchronization and memory recall with the OpenViking system. This tool is triggered by specific operator commands (`ov dream` or `ov recall <query>`), allowing users to sync chat transcripts or search past knowledge without interrupting the normal chat context flow. Ideal for data pipeline operations and knowledge base management.