Research

This skill provides automated tools for searching Google Scholar and PubMed, extracting citation metadata, validating references, and generating BibTeX entries. It includes detailed workflows for paper discovery, metadata extraction, and citation validation with practical scripts and checklists for academic writing.

Biomni is an autonomous AI agent framework for biomedical research that executes multi-step tasks across genomics, drug discovery, and clinical analysis. It decomposes complex queries, generates analysis code, retrieves from integrated databases, and produces research reports. The tool handles CRISPR design, single-cell RNA-seq, GWAS interpretation, and multi-omics integration with specific workflow examples.

Provides direct REST API access to PubMed with detailed guidance on constructing Boolean/MeSH queries, using E-utilities, and managing citations. Includes specific workflows for systematic reviews and programmatic data extraction with practical examples and rate limit handling.

This skill provides unified access to search academic papers across six major platforms including arXiv and PubMed. It defines clear trigger phrases for when users need to find research papers. The skill helps researchers avoid switching between different search interfaces.

This skill helps researchers refine vague questions into structured prompts for deep research tools. It asks clarifying questions about scope, format, and sources before generating detailed research task specifications. The tool enforces discipline in research question formulation.

This skill provides Python scripts and templates for creating publication-ready scientific figures. It includes journal-specific style presets, colorblind-safe palettes, and export functions for PDF/EPS/TIFF formats. The documentation covers multi-panel layouts, error bars, significance markers, and workflows for Nature/Science submissions.

A well-structured SERP analysis framework providing systematic methodology for intent classification, feature identification, and competitive analysis with clear output templates.

This skill wraps the pysam Python library for genomic data processing. It provides direct access to read/write SAM/BAM/CRAM alignment files, VCF/BCF variant files, and FASTA/FASTQ sequences. Includes examples for common bioinformatics tasks like extracting reads, calculating coverage, and merging VCF files.

A sophisticated research synthesis tool that provides comprehensive methodology for integrating findings from multiple agents, resolving contradictions, and generating structured reports with clear quality metrics.

A comprehensive competitive intelligence framework with clear processes for landscape mapping, feature comparison, win/loss analysis, battlecard creation, and ongoing tracking.

This skill fetches recent PubMed papers on biomedical topics and generates structured summaries in plain English. It follows a clear template, defines technical terms, and includes disclaimers. It requires local Python script execution.

This skill provides a structured workflow for generating scientific hypotheses from observations. It guides users through literature search, evidence synthesis, hypothesis formulation, prediction development, and experimental design. Outputs are formatted as LaTeX documents with visual schematics, following a systematic scientific method approach.