全部能力

Based on the Recursive Language Models (RLM) research by Zhang, Kraska, and Khattab (2025), this skill provides strategies for handling tasks that exceed…

Retrieve stock price change statistics across multiple time periods using Octagon MCP. Use when analyzing short-term and long-term returns, comparing…

Generate an energy-optimized, time-blocked daily plan based on circadian rhythm research and GTD principles

Check Meilisearch index status, tasks, health, and settings. Use for debugging search issues, monitoring indexing tasks, and inspecting index configuration.…

Conducts thorough landscape research, competitive analysis, best practices evaluation, and evidence-based recommendations. Expert in market research and trend…

Retrieve year-over-year growth in cash flow metrics including Operating Cash Flow, Free Cash Flow, and Net Cash Flow. Use when analyzing company cash…

Research topics and produce comprehensive written documentation. Synthesizes information into clear, well-structured, authoritative content pieces.

Retrieve comprehensive year-over-year growth in key financial metrics including Revenue, Gross Profit, Operating Income, Net Income, EPS, and Free Cash Flow.…

Retrieve year-over-year growth in income statement items including Revenue, Gross Profit, Operating Income, Net Income, and EPS Diluted. Use when analyzing…

PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector setup, indexing (HNSW, IVFFlat), hybrid search (FTS + BM25 + RRF), ParadeDB as Elasticsearch alternative, and re-ranking with Cohere/cross-encoders. Supports vector(1536) and halfvec(3072) types for OpenAI embeddings. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, Voyage rerank, graceful fallback, iterative_scan, filtered HNSW, websearch_to_tsquery, unaccent, multilingual FTS, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch, evaluation, benchmarking, Hit@K, MRR, contextual embeddings, halfvec cast

Retrieve stock price data and performance metrics using Octagon MCP. Use when analyzing daily closing prices, trading volume, price trends, historical…

Retrieve sector P/E ratios using Octagon MCP. Use when comparing company valuations to sector benchmarks, analyzing sector valuations across exchanges, and…

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

You must use this when synthesizing existing knowledge, identifying research gaps, or tracing the evolution of scientific ideas.

Creative writing skill for creating canonical reference documentation (wikis) for fictional worlds, characters, and story events. Use when creating or updating…

Document undocumented public APIs in PyTorch by removing functions from coverage_ignore_functions and coverage_ignore_classes in docs/source/conf.py, running…

Knowledge management skill for capturing, classifying, searching, and syncing project knowledge. Use when storing learnings, syncing BKD issue outcomes, or…

Use when analyzing Xiaohongshu account performance, tracking content metrics, researching competitors, or making data-driven decisions to optimize content…

Enrich contact, company, and influencer data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Resolving person identity and enriching consumer profiles (Minerva) - Searching for people or companies by criteria - Verifying email deliverability before outreach - Enriching influencer/creator profiles across social platforms TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" - "verify email", "check email", "is this email valid" - "influencer", "creator", "influencer contact", "influencer marketing"

Use when text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline…