383 boosters for "data" — open source, verified from GitHub, ready to install
Ray is an expert booster for Apache Ray distributed computing that helps developers convert Python code to Ray workloads, debug applications, and optimize performance across Ray's ecosystem (Core, Data, Train, Serve, Tune). Ideal for ML engineers and Python developers scaling computations from single machines to clusters.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
A pattern detection skill that determines whether specific entities, conditions, or signals exist in data sources, returning binary presence/absence results with confidence scores. Useful for developers building search, validation, and anomaly detection features into Claude-powered applications.
SWR is a React hook library for efficient data fetching with built-in caching, revalidation, and real-time updates. Developers building API-driven applications benefit from simplified server state management and automatic synchronization.
Analyze, review, and provide recommendations for distributed system designs. Use when: (1) Reviewing existing system architectures for gaps or improvements, (2) Analyzing system designs for scalability, reliability, or performance issues, (3) Providing recommendations on load balancing, caching, databases, sharding, replication, messaging, rate limiting, authentication, resilience, or monitoring, (4) Assessing trade-offs in system design decisions, (5) Creating system design review documents with gaps and recommendations. Triggers: "review my system design", "analyze this architecture", "what are the gaps", "system design recommendations", "scalability review", "reliability analysis".
Research people and companies, add to CRM database with smart linking
A practical guide to Supervised Fine-Tuning using SFTTrainer and Unsloth optimizations, enabling developers to efficiently adapt pre-trained LLMs for instruction-following with 2x faster training. Ideal for ML engineers building custom instruction-tuned models and reasoning systems.
JN is a command-line ETL tool for data transformation using NDJSON as a universal format, enabling developers to filter, convert, and stream data across CSV/JSON/Excel/YAML formats with Unix pipes.
Use this skill for analysis-only work and fresh workflow bootstrap. In this repository, use the repo-root wrapper: Run outside sandboxed environments by default. Do not first attempt the Playwright crawl inside the sandbox and then retry after it is intercepted.
"name": "webflow-mcp-server", "bin": "dist/index.js", "start": "concurrently \"npm run dev:local\" \"npm run inspector:local\"",
A progressive-disclosure skill for ROS 2 development — from first workspace to production fleet deployment. Each section below gives you the essential decision framework; detailed patterns, code templates, and anti-patterns live in the
"name": "@paretools/jvm", "version": "0.16.1", "mcpName": "io.github.Dave-London/pare-jvm",
Nuxt SEO is a meta-module that streamlines SEO configuration, sitemap generation, OG image creation, and structured data management for Nuxt applications. Developers building Nuxt sites need this to ensure proper search engine visibility and social media optimization.
"name": "claude-seo-assistant", "description": "权威性 SEO 助手工具，支持 Next.js 项目的元数据优化、结构化数据、内容审计、客座博客搜索、站外 SEO 和本地 SEO 分析", "author": "Claude Code SEO Team",
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Swift MCP Server provides structured access to Swift build, test, and package manager data for AI agents, enabling seamless integration with Claude, Cursor, and Copilot for iOS/macOS development workflows.
Run AI agents in parallel. Create agents with roles, trigger them on demand or on a schedule, and collect results. If this succeeds, skip to Step 3. If npm is not available, build from source:
"description": "Independent, unofficial Kaggle.com workflow plugin: competition reports, dataset/model downloads, notebook execution, forums, writeups, submissions, and badge collection. Not affiliated with, endorsed by, or sponsored by Kaggle or Google.", "homepage": "https://github.com/shepsci/kag
anyclaw turns any API, website, or CLI tool into agent-ready commands. Use it to search for packages, install them, and run commands directly from the terminal. Common packages you can install: Run or to discover more.
AniList MCP Server enables Claude to access AniList's anime and manga database through the Model Context Protocol, allowing developers and anime enthusiasts to integrate rich AniList data into AI-powered applications.
An MCP server that enables Claude to maintain persistent long-term and short-term memory across conversations using a local SQLite database. Developers and AI agents benefit from enhanced context retention and conversation continuity.
is discouraged in new packages and tolerated in existing packages. The SDK aims to minimize third-party dependencies. Table-driven tests are preferred for API client methods:
Use this skill to produce transparent, source-grounded fact-checking work. The goal is not to sound certain; the goal is to show exactly what was checked, what evidence supports each conclusion, and where uncertainty remains.
<!-- Real instructions live in config/config.md and meta/instructions/general.md. This file only bootstraps Windsurf into those. --> Check whether exists. If it does, you are in framework mode — this repo is being used to develop or maintain the llm-context-base framework itself, not as a personal
