Explore our collection of Agent Skills to enhance your AI workflow.
Organizes files and folders intelligently by understanding context, finding duplicates, and automating digital cleanup tasks.
Reads, writes, and manipulates DICOM medical imaging data, including pixel arrays, metadata extraction, and file anonymization.
Infers gene regulatory networks from expression data using high-performance machine learning algorithms like GRNBoost2 and GENIE3.
Recovers passwords and sensitive authentication data from disk images, corrupted files, and forensic scenarios using systematic analysis and specialized tools.
Analyzes chess board images to identify piece positions and calculate optimal moves using systematic image detection and engine-based verification.
Builds robust gRPC-based key-value store services in Python using protocol buffer schemas and standardized implementation patterns.
Integrates state-of-the-art machine learning models for NLP, computer vision, and audio tasks using the Hugging Face ecosystem.
Facilitates the retrieval and analysis of over 200 million AI-predicted protein structures from the AlphaFold DB for biological research and drug discovery.
Guides the development of self-interpreting Scheme-like evaluators through incremental implementation and systematic multi-level debugging.
Configures automated Git-based deployment systems that map specific repository branches to web-accessible directories using post-receive hooks.
Streamlines the creation of professional internal business communications using standardized organizational templates.
Generates standardized Terraform module structures with pre-configured core files and best-practice templates for cloud infrastructure.
Queries the STRING database to analyze protein-protein interaction networks and perform comprehensive functional enrichment for systems biology.
Performs advanced astronomical data analysis, coordinate transformations, and cosmological calculations using the industry-standard Astropy library.
Simplifies the conversion of chemical structures into machine learning-ready numerical features using over 100 diverse featurizers.
Enables parallel and distributed computing in Python to scale pandas and NumPy operations beyond memory limits.
Guides the development, structuring, and packaging of custom Claude Code skills using standardized templates and modular resource management.
Automates electronic lab notebook management through the LabArchives REST API for programmatic research documentation and data backup.
Applies medicinal chemistry rules and structural alerts to triage and prioritize compound libraries for drug discovery workflows.
Automates the creation of professional PDF documents, reports, and invoices using the robust ReportLab Python toolkit.
Debugs complex memory crashes in C++ applications related to custom allocators, static destruction ordering, and discrepancies between build configurations.
Facilitates high-quality code reviews by providing actionable frameworks for identifying bugs, ensuring architectural consistency, and delivering constructive feedback.
Accelerates drug discovery and molecular research by providing specialized tools for graph neural networks, protein modeling, and chemical property prediction.
Streamlines the finalization of development tasks by verifying tests and providing structured options for merging, pushing, or cleaning up Git branches.
Manages large-scale N-dimensional arrays with chunking and compression for high-performance scientific computing and cloud storage.
Implements custom compression encoders that ensure bit-level compatibility with existing decompressors and state-sensitive arithmetic coding logic.
Implements comprehensive evaluation frameworks for LLM applications using automated metrics, human feedback, and comparative benchmarking.
Streamlines the creation, organization, and management of production-ready Helm charts for Kubernetes application deployment.
Dispatches a specialized subagent to analyze code implementations against requirements and catch bugs before they cascade.
Implements advanced multi-objective and many-objective optimization frameworks using state-of-the-art evolutionary algorithms and Pareto analysis.
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