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Found 329 Skills
Master Node.js streams for memory-efficient processing of large datasets, real-time data handling, and building data pipelines
Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. it is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Evaluates and optimizes agent skills using a DSPy-powered GEPA (Generate/Evaluate/Propose/Apply) loop. Loads scenario YAML files as DSPy datasets, scores outputs with pattern-matching metrics, and optimizes prompts via BootstrapFewShot or MIPROv2 teleprompters. Also generates new scenario YAML files from skill descriptions.
Complete Development Guide for Tables, Search, and Pagination Features in React/Next.js Projects. Covers core technologies such as race condition handling, search system implementation, pagination systems, infinite scrolling, CRUD synchronization, Intersection Observer API, and state management selection. Key Features: - Handle race condition issues in asynchronous requests - Implement high-performance search and autocomplete features - Build professional-grade pagination systems and caching strategies - Develop smooth infinite scrolling experiences - Ensure data consistency for CRUD operations - Select the most suitable state management solution Applicable Scenarios: - React/Next.js applications requiring search and pagination features - List display and CRUD operations for large datasets - Need for high-performance infinite scrolling or virtualized lists - Facing complex data management issues such as race conditions and state synchronization - Projects needing to select an appropriate state management solution
Verify that claims and direct quotes in research manuscripts are present in source materials. Systematically checks interview transcripts, datasets, or cited literature using fast search with haiku agent fallback for intensive reading.
LLM fine-tuning expert for LoRA, QLoRA, dataset preparation, and training optimization
Blockchain analytics via Dune REST API — execute DuneSQL queries against live on-chain data, discover decoded contract tables, and monitor credit usage. Use when the user asks about on-chain data, wallet activity, DEX trades, token transfers, smart contract events, or says "query Dune", "run a Dune query", or "search Dune datasets". Pairs with MoonPay to analyze wallets you create and fund.
Overview The Amazon Agent is a high-performance tool designed to turn massive e-commerce datasets into structured, usable intelligence. It allows users to extract data from Amazon to monitor pricing,
Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.
Implements Syncfusion WinUI Cartesian Charts (SfCartesianChart) for data visualization in WinUI applications. Use this when working with column, line, bar, area, or financial charts (OHLC, Candle). This skill covers axis configuration, legends, tooltips, zooming/panning, data labels, and high-performance fast series for large datasets.
Implement and configure Syncfusion MultiColumnComboBox control in Windows Forms - an advanced combobox with multiple columns in dropdown and virtual data binding for large datasets. Use when creating dropdown lists with multiple data fields, DataSource binding, DisplayMember/ValueMember configuration, or column headers in dropdown. Covers filtered dropdown lists and replacing standard ComboBox with multi-column alternatives.
Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.