全部能力

Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral…

Research any topic across Reddit, X, and web from the last 30 days. Get current trends, real community sentiment, and actionable insights in 7 minutes vs 2…

Retrieve real-time or historical cash flow statement data including Net Income, Operating Cash Flow, Investing Cash Flow, Financing Cash Flow, Free Cash Flow,…

Analyze product reviews across any e-commerce platform. Extract actionable insights from customer feedback including pain points, praise patterns, feature…

RAG and search engineering — chunking, hybrid retrieval, reranking, and nDCG evaluation. Use when building retrieval-augmented generation pipelines.

AWS cost optimization and FinOps workflows. Use for finding unused resources, analyzing Reserved Instance opportunities, detecting cost anomalies, rightsizing…

Analyze earnings call transcripts to extract key insights about future guidance, strategic priorities, management commentary, and market signals.

Creates clear, concise technical documentation for software projects, runbooks, and developer guides.

Expert technical documentation specialist for developer docs, API references, and runbooks. Activate on: documentation, docs, README, API reference, technical…

Search and retrieve academic papers from arXiv.org using WebFetch and Exa. No MCP server required - uses existing tools to access arXiv API directly.

Designs production-grade RAG pipelines with chunking optimization, retrieval evaluation, and pipeline architecture. Use when building a RAG system, selecting a chunking strategy, choosing a vector database, optimizing retrieval quality, designing embedding pipelines, or evaluating RAG performance with RAGAS metrics.

This skill should be used when user asks to "search for papers", "find research papers", "search arXiv", "search PubMed", "find academic papers", "search…

Implements knowledge graphs for AI-enhanced relational knowledge. Covers ontology design, graph database selection (Neo4j, Neptune, ArangoDB, TigerGraph), entity extraction, hybrid graph-vector architecture, query patterns, and AI integration. Use when implementing knowledge graphs, designing ontologies, extracting entities and relationships, selecting a graph database, or building hybrid graph-vector search. Use for knowledge graph, ontology design, entity resolution, graph RAG, hallucination detection. For architecture selection and governance, use the knowledge-base-manager skill. For document retrieval pipelines, use the rag-implementer skill.

Comprehensive knowledge of GitHub Copilot SDK for embedding Copilot's agentic workflows in Python, TypeScript, Go, and .NET applications. Auto-activates for…

Expert knowledge for Azure Container Apps development including troubleshooting, best practices, decision making, architecture & design patterns, limits &…

Research and investigate business prospects and leads. Gathers company information, contact details, and qualification data for sales.

Generate research questions from economic phenomena

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS",…

Pre-ingestion verification for epistemic quality in RAG systems. Ensures documents are properly qualified before entering knowledge bases. Produces CGD (Clarity-Gated Documents) and validates SOT (Source of Truth) files.

Project memory system - save and search past decisions, preferences, context, and notes. Use when user says "remember this", asks "what did we decide about X",…