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This skill should be used when building AI agents using prompt-native architecture where features are defined in prompts, not code. Use it when creating autonomous agents, designing MCP servers, implementing self-modifying systems, or adopting the "trust the agent's intelligence" philosophy.

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.

This skill should be used when writing Ruby gems following Andrew Kane's proven patterns and philosophy. It applies when creating new Ruby gems, refactoring existing gems, designing gem APIs, or when clean, minimal, production-ready Ruby library code is needed. Triggers on requests like "create a gem", "write a Ruby library", "design a gem API", or mentions of Andrew Kane's style.

Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.

Guidelines for writing folder READMEs. Use when creating README.md files for directories.

Git commit and pull request guidelines using conventional commits. Use when creating commits, writing commit messages, creating PRs, or reviewing PR descriptions.

GitHub issue comment guidelines for community interaction. Use when responding to GitHub issues, bug reports, feature requests, or any GitHub discussion.

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

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.

Technical writing, README guidelines, and punctuation rules. Use when writing documentation, READMEs, technical articles, or any prose that should avoid AI-generated feel.

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

Social media post guidelines for LinkedIn, Reddit, and Twitter/X. Use when drafting posts, announcements, or sharing technical content on social platforms.

This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions

Build and run LLM-powered data processing pipelines with DocETL. Use when users say "docetl", want to analyze unstructured data, process documents, extract information, or run ETL tasks on text. Helps with data collection, pipeline creation, execution, and optimization.

Run unit tests that require the Spanner emulator. Use this skill when the user wants to run tests in packages like satellite/metabase, satellite/metainfo, or any other tests that interact with Spanner. Automatically handles checking for and configuring the Spanner emulator environment.

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.

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.

Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.