代码生成
生成代码、脚手架和模板
gpui-context
longbridge
Context management in GPUI including App, Window, and AsyncApp. Use when working with contexts, entity updates, or window operations. Different context types provide different capabilities for UI rendering, entity management, and async operations.
gpui-action
longbridge
Action definitions and keyboard shortcuts in GPUI. Use when implementing actions, keyboard shortcuts, or key bindings.
gpui-entity
longbridge
Entity management and state handling in GPUI. Use when working with entities, managing component state, coordinating between components, handling async operations with state updates, or implementing reactive patterns. Entities provide safe concurrent access to application state.
github-pull-request-description
longbridge
Write a description to description GitHub Pull Request.
generate-component-documentation
longbridge
Generate documentation for new components. Use when writing docs, documenting components, or creating component documentation.
gpui-test
longbridge
Writing tests for GPUI applications. Use when testing components, async operations, or UI behavior.
gpui-focus-handle
longbridge
Focus management and keyboard navigation in GPUI. Use when handling focus, focus handles, or keyboard navigation. Enables keyboard-driven interfaces with proper focus tracking and navigation between focusable elements.
generate-component-story
longbridge
Create story examples for components. Use when writing stories, creating examples, or demonstrating component usage.
gpui-element
longbridge
Implementing custom elements using GPUI's low-level Element API (vs. high-level Render/RenderOnce APIs). Use when you need maximum control over layout, prepaint, and paint phases for complex, performance-critical custom UI components that cannot be achieved with Render/RenderOnce traits.
gpui-style-guide
longbridge
GPUI Component project style guide based on gpui-component code patterns. Use when writing new components, reviewing code, or ensuring consistency with existing gpui-component implementations. Covers component structure, trait implementations, naming conventions, and API patterns observed in the actual codebase.
astropy
K-Dense-AI
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
generate-image
K-Dense-AI
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.
clinical-decision-support
K-Dense-AI
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
benchling-integration
K-Dense-AI
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
datamol
K-Dense-AI
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.
cirq
K-Dense-AI
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
flowio
K-Dense-AI
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.
dnanexus-integration
K-Dense-AI
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.
denario
K-Dense-AI
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
K-Dense-AI
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
brenda-database
K-Dense-AI
Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.
PRD to Issues
mattpocock
Do NOT close or modify the parent PRD issue.
Scaffold Exercises
mattpocock
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obsidian-vault
mattpocock
Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.