Skill UI

LaminDB is an open-source lineage-native lakehouse designed for biological datasets and models. It enables queryable, traceable, and validated data management across various storage formats like S3 and Postgres. Users can track computational workflows, curate data with ontologies via Bionty, and ensure FAIR compliance. Ideal for managing scRNA-seq, spatial transcriptomics, and integrating ML pipelines while maintaining reproducibility and collaboration.

Perform differential gene expression analysis for bulk RNA-seq with PyDESeq2, including formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.

Scanpy is a scalable Python toolkit for single-cell RNA-seq analysis, covering quality control, normalization, dimensionality reduction, clustering, and visualization. It supports converting R formats to h5ad and includes ready-to-run CLI scripts for end-to-end workflows, making it ideal for exploratory scRNA-seq analysis and publication-quality plotting.

scVelo is a Python package for RNA velocity analysis in single-cell RNA-seq data. It estimates cell state transitions from unspliced/spliced mRNA dynamics, infers trajectory directions, computes latent time, and identifies driver genes to reveal cell fate decisions.

scvi-tools is a comprehensive Python framework for probabilistic deep generative models in single-cell genomics. Built on PyTorch and PyTorch Lightning, it enables batch correction, transfer learning, differential expression analysis with uncertainty, and multi-modal data integration. Best for advanced modeling of single-cell RNA-seq, ATAC-seq, CITE-seq, spatial transcriptomics, and specialized modalities like methylation and cytometry.

This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.

This internal agent skill automates the complex process of determining the most likely owner or team for a bug cluster. It follows a strict 6-level precedence model, starting with cached overrides, and sequentially querying sources like Service Owners, Oncall status, CODEOWNERS, recent assignees, and committers. The process includes staleness detection and confidence scoring, providing highly accurate and auditable routing recommendations for internal development triage.

This technique guides users through a rigorous two-phase research strategy. First, conduct a broad search to identify potential papers or authors. Crucially, the system instructs the user to use the extracted "author full name" as a highly specific anchor in subsequent queries. Combining the author's name with details like journal, institution, year, or biographical information ensures the most precise and reliable results, significantly narrowing down the search scope and achieving deep academic insights.

An end-to-end orchestrator for bulk RNA-seq analysis, guiding users from raw FASTQ reads through QC, alignment, quantification, and differential expression. It supports both nf-core/rnaseq and standalone tools like STAR/Salmon, ensuring reproducible and statistically sound results for gene-level counts and pathway enrichment.

This skill provides comprehensive auditing of Fabric and Power BI tenant settings against a curated governance baseline. It detects configuration 'drift,' enumerates delegated overrides across capacity, domains, and workspaces, and investigates associated Entra security groups. It translates complex API findings into grounded, actionable discussions, helping users understand functional consequences and risks.

This foundational skill guides the establishment and maintenance of a comprehensive developer audience context. It helps map out detailed developer personas, identify core pain points, analyze current alternatives, and determine key technical differentiators. By structuring this context across 10 critical sections, it ensures all subsequent developer marketing materials are highly targeted and speak the exact language of the target user.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.