Skill UI

Access DepMap data to fetch CRISPR Chronos dependency scores, drug sensitivity readouts, and gene effect profiles for cancer cell lines, supporting target validation, biomarker discovery, and synthetic-lethality research via API or downloads.

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.

Query the PrimeKG precision medicine knowledge graph to explore genes, drugs, diseases, phenotypes, and their relationships, supporting drug discovery, repurposing, and phenotype analysis through programmatic scripts.

A comprehensive guide for defining, tracking, and interpreting product metrics across all stages—from discovery to maturity. This skill covers selecting metric frameworks (AARRR, HEART), defining stage-appropriate KPIs, designing multi-layered dashboards, and executing deep analyses like cohort and retention modeling. It helps teams transform raw data into actionable product strategies, moving beyond vanity metrics.

A comprehensive toolset for digital forensics investigators, enabling the parsing of proprietary Microsoft Outlook PST and OST files. It extracts critical evidence including full message content, detailed email headers (for message routing/tracing), attachments, and deleted items from the Recoverable Items folder. Essential for e-discovery, legal investigations, and security incident response to reconstruct communication patterns and analyze message metadata.

Automates GA4 reporting and property management via Composio’s Rube MCP, covering account/property discovery, standard/batch/pivot/funnel reports, and key event workflows so analysts can run repeatable queries without manual UI steps.

Pythonic RDKit wrapper for molecular cheminformatics: parse and standardize SMILES, compute descriptors and fingerprints, cluster compounds, generate 3D conformers, and run parallel drug-discovery workflows.

Python library for medicinal chemistry filtering of compound libraries. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alerts (PAINS, NIBR, ChEMBL), complexity metrics, chemical group detection, and a query language for large-scale molecular triage in drug discovery.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. It enables pKa prediction, molecular docking, conformer search, and protein-ligand cofolding without local HPC infrastructure. Ideal for batch screening and multi-step chemistry pipelines in drug discovery.

This skill leverages the Gemini AI model to perform comprehensive and broad literature discovery across academic domains. Unlike traditional APIs, it decomposes complex research queries into sub-problems, explores topic aliases, and surfaces highly relevant papers that might otherwise be missed. It is ideal for conducting deep, multi-angled literature reviews and achieving a holistic view of a research field.

This skill provides expert, guided assistance for creating, auditing, and improving Best Practice Analyzer (BPA) rules for Power BI semantic models. It utilizes an interactive, double-diamond discovery process to gather deep context about your organizational standards, model structure, and business goals before generating tailored, reusable data validation and governance rules.

This skill provides a comprehensive, step-by-step workflow for building complete Power BI reports from scratch using the pbir CLI. It guides users through model discovery, defining design briefs, visual layout, data validation, and final publishing. Ideal for automating the entire business intelligence (BI) reporting process and ensuring adherence to professional design standards.