全部能力

Audit design token usage across a product for consistency and coverage.

Comprehensive scientific literature search across PubMed, arXiv, bioRxiv, medRxiv. Natural language queries powered by Valyu semantic search.

Research competitors and compare positioning, messaging, content strategy, and market presence. Use when analyzing a competitor, building battlecards,…

Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want…

Design gesture-based interactions for touch and pointer devices.

Design system feedback for user actions including confirmations, status updates, and notifications.

Create developer handoff specifications with measurements, behaviors, assets, and edge cases.

Sports news via RSS/Atom feeds and Google News. Fetch headlines, search by query, filter by date. Covers football news, transfer rumors, match reports, and any sport via Google News. Use when: user asks for recent news, headlines, transfer rumors, or articles about any sport. Good for "what's the latest on [team/player]" questions. Supports any Google News query and curated RSS feeds (BBC Sport, ESPN, The Athletic, Sky Sports). Don't use when: user asks for structured data like standings, scores, statistics, or xG — use the sport-specific skill instead: football-data (soccer), nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), nhl-data (NHL), mlb-data (MLB), tennis-data (tennis), golf-data (golf), cfb-data (college football), cbb-data (college basketball), or fastf1 (F1). Don't use for prediction market odds — use polymarket or kalshi. News results are text articles, not structured data.

Cubox CLI is a callable personal reading memory system that enables you to search, read, and use saved content, perform semantic (RAG-based) queries, access…

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function…

Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, embedding documents, implementing hybrid search,…

Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.

Visualizes Azure infrastructure from ARM templates, Azure CLI, or descriptions. Use when user has Azure resources to diagram.

Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.

Use when auditing the codebase through the evaluation platform with mandatory research, coordinated domain audit workers, and structured summaries.

Configure PostgreSQL with pgvector for GrepAI. Use this skill for team environments and large codebases.

Creates complete project documentation system (project docs, reference, tasks, tests). Use when bootstrapping docs from scratch or regenerating all.

Expert personal finance coach with deep knowledge of tax optimization, investment theory (MPT, factor investing), retirement mathematics (Trinity Study, SWR…

File system operations guidance - read, write, search, and manage files using Claude Code's built-in tools.

Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM…