Development

This skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers (OpenAI, Anthropic, Gemini, Ollama), building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.

This skill should be used when creating distinctive, production-grade frontend interfaces with high design quality. It applies when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

TypeScript code style, type co-location, constant naming conventions, and arktype patterns. Use when writing TypeScript code, defining types, creating constants, or working with arktype schemas.

CSS and Tailwind styling guidelines. Use when writing styles, creating UI components, reviewing CSS/Tailwind code, or deciding on wrapper element structure.

Behavioral guideline for providing brutally honest feedback. Use always - this skill defines core interaction expectations for code review and technical discussions.

Error handling patterns using wellcrafted trySync and tryAsync. Use when writing error handling code, using try-catch blocks, or working with Result types and graceful error recovery.

Apply factory function patterns to compose clients and services with proper separation of concerns. Use when creating functions that depend on external clients, wrapping resources with domain-specific methods, or refactoring code that mixes client/service/method options together.

Rust to TypeScript error handling patterns for Tauri apps. Use when defining Rust errors that will be passed to TypeScript, handling Tauri command errors, or creating discriminated union error types.

Monorepo script commands and conventions for this codebase. Use when running builds, tests, formatting, linting, or type checking.

Svelte 5 patterns including TanStack Query mutations, shadcn-svelte components, and component composition. Use when writing Svelte components, using TanStack Query, or working with shadcn-svelte UI.

Human-readable control flow patterns for refactoring complex conditionals. Use when refactoring nested conditionals, improving code readability, or restructuring decision logic.

This skill should be used when drafting GitHub issues for the Positron repository. It provides workflows for searching duplicates, selecting appropriate labels, gathering complete context through questioning, and writing terse, fluff-free issues that precisely describe what is needed or wrong. The skill prepares issues for manual submission by the user. Use this skill when the user asks to draft or prepare an issue for Positron.

This skill should be used when developing, debugging, or maintaining Positron Notebooks - the React-based feature-flagged notebook editor. Load this skill when tasks involve notebook cells, execution, selection state, context keys, or notebook editor features.

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

Comprehensive code review for GitHub pull requests using parallel agents. Checks bugs, CLAUDE.md compliance, git history, previous PR patterns, and code comments. Use when reviewing PRs, doing code review, or when user mentions "review PR", "check PR", or provides a PR number.

Interact with Storj Gerrit team code collaboration service, which we just called it gerrit, when the user ask to do it

Applies Notion Avatar's hand-drawn minimalist style to any artifact that may benefit from having the project's look-and-feel. Use it when brand colors, style guidelines, visual formatting, or design standards apply.

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.