133 boosters for "graph" — open source, verified from GitHub, ready to install
This skill provides the official Vibecode brand design system. Follow these guidelines when creating or styling UI components. Vibecode is a modern, tech-forward brand emphasizing clarity, accessibility, and innovation. Focus on creating intuitive digital experiences while maintaining visual consist
"name": "langchain-skills", "description": "Agent skills for building agents with LangChain, LangGraph, and Deep Agents", "name": "LangChain",
45 AI-powered skills for affiliate marketers. Each skill automates a specific workflow (content creation, program research, SEO, outreach, analytics, etc.) using live data from the Affitor API.
An X-ray Diffraction analysis skill that enables automated crystal structure identification, phase analysis, and crystallite size determination for nanomaterials research. Ideal for materials scientists, chemists, and nanotechnology researchers working with XRD data.
"name": "shopify-plugin", "description": "Shopify developer tools for Claude Code — search Shopify docs, generate and validate GraphQL, Liquid, and UI extension code. Skill scripts send usage telemetry (queries, code, model/client identifiers) to shopify.dev by default; set OPTOUTINSTRUMENTATION=tru
Graphlit MCP Server integrates the Graphlit knowledge graph platform with Claude, enabling developers to build AI agents with RAG capabilities, document parsing, and intelligent retrieval. It's ideal for teams building document-heavy AI applications, knowledge management systems, and enterprise AI agents.
LC-StudyLab provides Cursor IDE rules and documentation links for LangChain v1.0, enabling developers to quickly reference core components and advanced features while coding with LangChain's full ecosystem.
This skill provides comprehensive guidance for all aspects of Playwright test development, from writing new tests to debugging and maintaining existing test suites. Consult these references based on what you're doing:
This repository root file is a lightweight pointer. The executable skill lives in . Load only when needed: Full website (Gallery, PBL, knowledge map, APIs) lives in the courseware repository:
Generate e-commerce images using GPT-Image-2 via Codex CLI. Match user intent to structured JSON prompt templates, assemble concise prompts, and invoke image generation. From the user's request, extract: If the user provides a product photo path, note it for parameter.
Graphsignal observes inference workloads from a sidecar process — the profiler. It never shares a process with CUDA: the profiler watches the workload externally via CUPTI, OTLP/gRPC, Prometheus scraping, and NVML. Auto-instrumentation covers vLLM, SGLang, and PyTorch out of the box. Two install pat
"version": "0.46.0", "description": "Build and deploy web apps and agents", "url": "https://github.com/vercel"
You are an expert CTF competitor and challenge solver with deep experience across all major CTF platforms including HackTheBox, TryHackMe, PicoCTF, OverTheWire, VulnHub, and competitive jeopardy and attack-defense CTFs. You operate as a methodical problem-solving partner, guiding users through chall
"name": "open-ontologies", "description": "A Terraforming MCP for Knowledge Graphs: validate, classify, and govern AI-generated ontologies.", "name": "fabio-rovai"
Quick reference for crypto CTF challenges. Each technique has a one-liner here; see supporting files for full details with code.
This skill encodes the complete design specification for professional business presentations — a consultant-grade PowerPoint framework based on McKinsey design principles. It includes: All specifications have been refined through iterative production feedback to ensure visual consistency, profession
ExRam.Gremlinq is a .NET object-graph-mapper (OGM) for Apache TinkerPop™ Gremlin-enabled graph databases. It translates strongly-typed C# LINQ-style queries into Gremlin bytecode/scripts and handles serialization/deserialization. The solution contains ~37 projects (17 src, 16 test, 1 templates, 3 te
用户说"想学 / 理解 / 搞懂 / 讲讲一个概念 X"时——这是默认入口，一次跑完五视角，用户再选深入哪个。 抓住 X 的本质结构（剥术语），按三猜想给 🎁其实已学过 / 🔗结构同构（字段级对应表）/ 🧩可用已有知识解释，点出元知识。先激发信心，再谈深入。 定位"既定问题"（学 X 解决什么）、现有知识够不够、X 的贬值速度与 ROI，给"够用就停 / 只学最小那块 / 值得深挖"的深度边界。不是劝退，是防止一上来过度钻。
用户要系统进入一个新领域，或焦虑"学得不够系统 / 不知何时算够"。 用户为什么学 X？（接 的"既定问题"）目的决定图谱画到多细。 从入门点出发、沿父子关系排一条有效路径。颗粒度按需自由切换（领域图 → 细分学科图）。"学到哪算够"= 覆盖到能解决第一步那个目的的节点即可，不必学满。
Refero gives agents taste and product evidence. Use it before design work instead of relying on generic model knowledge. Refero has three research layers:
A fully autonomous AI research agent that ingests sources into Google NotebookLM, runs deep web research, synthesizes knowledge through cited Q&A and 9 downloadable artifact types, creates polished content drafts, and optionally publishes to social platforms.
"name": "project-multilevel-index", "description": "分形多级索引系统 - 受《哥德尔、埃舍尔、巴赫》启发的自指文档系统。自动维护 PROJECTINDEX、FOLDERINDEX 和文件头注释，实现代码与文档的完美同步。", "name": "Claude Code Community",
This MCP server bridges AI assistants with Linear project management via GraphQL, enabling Claude and Cursor users to query and manage Linear projects directly through natural language. It's essential for teams using Linear who want AI-assisted workflow automation and issue management.
This skill generates reusable Relay-based Nodes components that: Activate this skill when users ask to: The skill automatically determines:
