Skill UI

Query the Monarch Initiative API to explore disease-gene-phenotype associations across species, enabling rare disease gene discovery, phenotype-to-gene mapping, and cross-species modeling via integrated HPO and model organism data.

This skill provides comprehensive functionality for querying, comparing, and calculating nutritional data from a structured food database. Users can perform precise searches by food name or nutritional criteria (e.g., high protein, low GI). It supports calculating total nutrient intake based on specific portions, suggesting foods for various health conditions (like diabetes or high blood pressure), and performing detailed comparative analysis between multiple food items.

A comprehensive tool for interacting with the arXiv database. It allows users to search for academic papers by topic or ID, retrieve detailed metadata (abstracts, authors, categories), and download the PDF files directly. Ideal for researchers and students needing to efficiently find, save, and summarize scientific literature.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

A comprehensive multi-phase tool designed to rigorously check the novelty of proposed research methods or technical ideas against current academic literature. It systematically extracts core claims, performs multi-source literature searches (including arXiv, major conferences, and web databases), and uses advanced cross-model verification to generate a structured, actionable Novelty Report, advising on the unique contribution and research positioning.

Provides REST API access to PubMed for building advanced Boolean/MeSH queries, filtering by publication details, and programmatically fetching citations through E-utilities, making it ideal for systematic reviews and automated literature workflows.

Provides direct REST API access to UniProt, the premier resource for protein sequence and functional information. This skill enables users to search proteins by name, gene, or accession number, retrieve sequences in FASTA format, perform cross-database ID mapping (e.g., Ensembl, RefSeq), and analyze functional annotations (GO terms) for building comprehensive bioinformatics pipelines.

A powerful tool designed for academic researchers and scientists. It searches a curated database of scientific literature and retrieves structured metadata and quantitative experimental data (including methods, results, sample sizes, and quality scores) directly from full-text papers, going far beyond simple abstracts. Ideal for systematic literature reviews, evidence synthesis, and meta-analyses requiring detailed, comparable study information.

BioServices provides Python wrappers for 40+ bioinformatics services, allowing cross-database queries, identifier mapping, pathway exploration, and sequence or compound research within consistent workflows.

This skill provides comprehensive, real-time research information lookup capabilities. It features intelligent backend routing, automatically selecting between fast general web search (primary), deep multi-source synthesis (for exhaustive research), or specialized academic database searches (for papers and scholarly articles). Ideal for literature verification, academic background research, and gathering market intelligence.

Access and query 78 public databases covering diverse fields including biomedical, physical sciences, earth science, and economics. This skill identifies the relevant database(s) for user queries (e.g., genes, compounds, patents, climate data, financial indicators), executes structured REST API calls, and returns raw JSON results, providing a comprehensive data retrieval pipeline.

This tool collects comprehensive diagnostic data from ClickHouse system tables. It gathers crucial metrics, query logs, merge statuses, and disk usage information. It is essential for troubleshooting performance bottlenecks, preparing detailed support tickets, or investigating complex database infrastructure issues.