全部能力

Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.

Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer…

Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical…

Build agentic AI with OpenAI Responses API - stateful conversations with preserved reasoning, built-in tools (Code Interpreter, File Search, Web Search), and MCP integration. Prevents 11 documented errors. Use when: building agents with persistent reasoning, using server-side tools, or migrating from Chat Completions/Assistants for better multi-turn performance.

Super LinkedIn for the terminal. Search, enrich, and map warm-intro paths across LinkedIn (stickerdaniel/linkedin-mcp-server subprocess), Happenstance…

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

Formal theorem proving with research, testing, and verification phases

Debug database performance issues through query analysis, index optimization, and execution plan review. Identify and fix slow queries.

Search Tool Hierarchy

Build RAG systems and semantic search with Gemini embeddings (gemini-embedding-001). 768-3072 dimension vectors, 8 task types, Cloudflare Vectorize integration. Prevents 13 documented errors. Use when: vector search, RAG systems, semantic search, document clustering. Troubleshoot: dimension mismatch, normalization required, batch ordering bug, memory limits, wrong task type, rate limits (100 RPM).

Manage local skills - list, add, remove, search, edit, setup wizard

Research-to-implement pipeline chaining 5 MCP tools with graceful degradation

Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which…

Search Tool Hierarchy

Semantic search, similar content discovery, and structured research using Exa API. Use when you need semantic/embeddings-based search, finding similar content,…

Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state…

Index at Creation Time

Build semantic search with Cloudflare Vectorize V2. Covers async mutations, 5M vectors/index, 31ms latency, returnMetadata enum changes, and V1 deprecation. Prevents 14 errors including dimension mismatches, TypeScript types, testing setup. Use when: building RAG or semantic search, troubleshooting returnMetadata, V2 timing, metadata index, dimension errors, vitest setup, or wrangler --json output.

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms.…

Automatically searches prior art via SerpAPI and generates Chinese patent application forms. This skill should be used when the user wants to generate Chinese…