Explore our collection of Agent Skills to enhance your AI workflow.
Models and analyzes interacting dynamical systems using algebraic structures and GF(3) conservation principles.
Manages the lifecycle and state transitions of Request for Comments (RFC) documents directly within your workspace.
Generates visual bifurcation diagrams to analyze parameter-dependent transitions in dynamical systems.
Synchronizes stacked git commits with the main branch using git-branchless to automate rebasing and conflict resolution.
Lists and tracks Product Requirement Documents with automated progress calculation and status filtering.
Generates detailed, research-backed user personas using structured templates and guided questions.
Recovers from Git mistakes and restores previous repository states using the powerful git-branchless undo system.
Builds and manages process-based discrete-event simulations in Python to model complex systems like manufacturing, logistics, and network traffic.
Manages git-branchless commits by recording changes and optionally creating branches while maintaining a detached HEAD state.
Accelerates scientific discovery by automatically generating, testing, and refining hypotheses from datasets and research literature using LLMs.
Extracts, reviews, and synchronizes developer feedback and skill improvements from Claude Code sessions to Product Forge or GitHub.
Enforces PEP 7 and PEP 8 compliance for CPython development, ensuring code quality and consistency across Python and C files.
Automates comprehensive code reviews within Claude Code to identify security vulnerabilities, logic bugs, and performance bottlenecks.
Runs Python code in the cloud with serverless containers, high-performance GPUs, and automatic scaling for AI/ML workloads.
Streamlines contributions to the CPython repository by providing codebase orientation and coordinating specialized build, style, and documentation workflows.
Automates programmable chemical synthesis using the XDL language and modular robotic hardware instructions.
Generates comprehensive, technical Feature Requirement Documents (FRDs) through a structured 12-step interactive session.
Performs fast nonlinear dimensionality reduction and manifold learning for high-dimensional data visualization and clustering.
Guides developers through structured technical brainstorming sessions to architect robust software solutions within Claude Code.
Ensures Python code quality and type safety through expert static analysis patterns and Mypy configuration.
Lists and filters technical Request for Comments (RFC) documents to track architectural decisions and project progress.
Provides programmatic Python access to over 40 bioinformatics web services for biological data retrieval and pathway analysis.
Facilitates machine learning for drug discovery using a PyTorch-based toolkit for molecular property prediction, protein modeling, and retrosynthesis.
Initializes a standardized infrastructure for multi-agent development workflows by creating a dedicated parallel processing directory.
Performs comprehensive single-cell RNA-seq analysis workflows including quality control, clustering, and cell type annotation.
Facilitates advanced biomedical literature research and programmatic access to the National Library of Medicine's PubMed database via E-utilities.
Enables high-performance data manipulation and analysis using the Polars DataFrame library's lightning-fast expression API.
Analyzes biological data using specialized tools for sequence manipulation, phylogenetics, and microbial ecology metrics.
Streamlines the creation, validation, and maintenance of CPython documentation using reStructuredText and NEWS entry standards.
Performs constraint-based metabolic modeling and systems biology simulations using the COBRApy Python library.
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