gget
Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
get-available-resources
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
geo-database
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
generate-image
Generate or edit images using AI models (FLUX, Gemini). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.
gene-database
Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.
fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
flowio
Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.
fda-database
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
exploratory-data-analysis
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
etetoolkit
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
esm
Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.
ensembl-database
Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.
ena-database
Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.
drugbank-database
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill should be used when working with pharmaceutical data, drug discovery research, pharmacology studies, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task requiring detailed drug and drug target information from DrugBank.
xlsx
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
PDF manipulation toolkit. Extract text/tables, create PDFs, merge/split, fill forms, for programmatic document processing and analysis.
docx
Document toolkit (.docx). Create/edit documents, tracked changes, comments, formatting preservation, text extraction, for professional document processing.
dnanexus-integration
DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
diffdock
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
denario
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
deeptools
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
deepchem
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
datamol
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
restcontroller-conventions
Specifies standards for RestController classes, including API route mappings, HTTP method annotations, dependency injection, and error handling with ApiResponse and GlobalExceptionHandler.
response-rater
Rates responses and plans against quality rubrics. Used for plan validation, response quality audits, and multi-agent consensus.
research-synthesis
Research best practices and synthesize into design decisions for artifact creation. Invoke BEFORE any creator skill to ensure research-backed decisions.
regulatory-compliance
Validate systems and processes against GDPR/CCPA privacy regulations, privacy-by-design principles, ADA/WCAG accessibility standards, data processing agreements (DPAs), and provide compliance checklists with regulatory change monitoring guidance.
reddit-researcher
Search and read public Reddit posts, subreddits, and comments via the unauthenticated JSON API. Safe read-only access with SSRF-prevention hostname allowlist.
recovery
Workflow recovery protocol for resuming workflows after context loss, session interruption, or errors. Handles state reconstruction, artifact recovery, and seamless workflow continuation.
recommend-evolution
Detect capability gaps and record standardized evolution recommendations.
readme
Use when creating, updating, or generating README and documentation files for projects and libraries
react-native-skills-vercel
React Native and Expo best practices for building performant mobile apps. Use
react-expert
React ecosystem expert including hooks, state management, component patterns, React 19 features, Shadcn UI, and Radix primitives
react-best-practices-vercel
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
ralph-loop
Autonomous iteration loop with dual-mode support. Standalone mode uses Stop hooks (RALPH_ACTIVE=1). Multi-agent mode uses router-managed iteration. Never traps the host/router session.
python-backend-expert
Python backend expert including Django, FastAPI, Flask, SQLAlchemy, and async patterns
protocol-reverse-engineering
Master network protocol reverse engineering including packet analysis, protocol dissection, and custom protocol documentation. Use when analyzing network traffic, understanding proprietary protocols, or debugging network communication.
property-based-testing
fast-check patterns for JS/TS — 6 canonical property categories with worked examples targeting agent-studio utilities (path normalization, safe-json, glob-to-regex, routing logic)
project-stage-detection
Detect project maturity stage (new/early/mid/mature) from file structure and route to appropriate onboarding workflow
project-onboarding
Guided project onboarding for new codebases. Helps agents understand project structure, build systems, test commands, and development workflows by creating persistent knowledge memories.
project-analyzer
Automated brownfield codebase analysis. Detects project type, frameworks, dependencies, architecture patterns, and generates comprehensive project profile. Essential for Conductor integration and onboarding existing projects.
proactive-audit
>-
prioritize-python-3-10-features
Prioritizes the use of new features available in Python 3.12 and later versions.
prd-generator
Generate structured Product Requirements Documents using hypothesis-driven methodology with Implementation Phases tracking.
pptx
PowerPoint presentation generation using python-pptx. Create slides from Claude output, data analysis, or structured content. Covers slide templates, shapes, charts, tables, and themed presentations. Use for generating .pptx files programmatically.
powershell-expert
PowerShell 7+ scripting and Windows system administration -- cross-platform automation, secure credential handling, Pester testing, DSC, and JEA patterns.
postmortem-writing
Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.
planning-with-files
Manus-style file-based planning for complex tasks. Use task_plan.md, findings.md, and progress.md to maintain persistent context. Use for multi-step tasks, research, or work spanning many tool calls.
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