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Found 213 Skills
Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.
AWS CloudFormation patterns for Lambda functions, layers, event sources, and integrations. Use when creating Lambda functions with CloudFormation, configuring API Gateway, Step Functions, EventBridge, SQS, SNS triggers, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for cold start optimization.
Create interactive maps with markers, heatmaps, routes, and choropleth layers. Use when visualizing geographic data, plotting locations, or creating map-based reports.
Optimize ToolUniverse skills for better report quality, evidence handling, and user experience. Apply patterns like tool verification, foundation data layers, disambiguation-first, evidence grading, quantified completeness, and report-only output. Use when reviewing skills, improving existing skills, or creating new ToolUniverse research skills.
Run a full-scale implementation review with parallel subagents for plan alignment, UI verification, technical and strategic analysis, and test coverage gap closure across app and database layers.
Build and structure React applications with TypeScript, Tailwind CSS, Recharts, and modern best practices. Use when creating React components, hooks, API layers, charts, dashboards, or when the user asks about React project structure, TypeScript patterns, or frontend architecture.
Evaluates and prevents unnecessary abstractions by analyzing interfaces, layers, and patterns against concrete requirements. Use when evaluating new abstractions, reviewing architecture proposals, detecting over-engineering, or simplifying existing code. Triggers on "is this abstraction necessary", "too many layers", "simplify architecture", "reduce complexity", "over-engineered", "do we need this interface", or when reviewing design patterns.
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
Implementation guide for Syncfusion WinForms Maps control - a geographical data visualization component that displays statistical and regional data using shape files, bubbles, markers, and interactive features. Use this when working with WinForms Maps, geographical maps in Windows Forms, shape file visualization, choropleth maps, or bubble maps. This skill covers map layers, zooming/panning, geographical data binding, ESRI shape files, and building location-based desktop applications with interactive maps.
Reverse Paper Reading Method: Given a paper, recursively identify the previous papers it critiques and improves on (max 5 layers), then find the latest research progress published after it, and tell the evolution history of the relevant problem forward from the source. Centered on problems, explain the problems identified by each paper and their solution innovations in a Feynman-style manner. Use when user shares a paper and wants to understand its intellectual lineage, citation chain, problem evolution, or says 'reverse reading', 'paper traceability', 'paper context', 'paper river', 'paper connects', 'trace back', 'the ins and outs of this paper', 'paper evolution'. Also trigger when user wants to understand how a research problem evolved across multiple papers.
Find dead code and cleanup candidates such as unused exports, unreachable branches, orphaned files, stale feature flags, dead registrations, and compatibility layers with no live callers. Use when auditing refactors, bundle-size cleanup, architecture simplification, pre-release cleanup, reviewing requests to find unused code or decide what can be deleted, or when deciding whether code can be safely removed or auto-fixed.
Expert DI decisions for iOS/tvOS: when DI containers add value vs overkill, choosing between injection patterns, protocol design for testability, and SwiftUI-specific injection strategies. Use when designing service layers, setting up testing infrastructure, or deciding how to wire dependencies. Trigger keywords: dependency injection, DI, constructor injection, protocol, mock, testability, container, factory, @EnvironmentObject, service locator