Search Agent Skills for Grok Build

Search across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical…

Query decomposition and multi-source search orchestration.

Seek and analyze video content using Memories.ai Large Visual Memory Model for persistent video intelligence

Implement efficient similarity search with vector databases.

Manages connected MCP sources for enterprise search.

Cluster code by graph community detection via npx ruvector@0.2.25 hooks graph-cluster (spectral / Louvain)

Optimize vector index performance for latency, recall, and memory.

First-run setup for ruvector@0.2.25 — installs ONNX/Brain/SONA add-ons, registers the MCP server, and verifies the install via `doctor`

Vector-powered CLI for semantic file search with a Claude/Codex skill

Search, query, and manage Weaviate vector database collections — semantic, hybrid and keyword search, filtered fetching, and data imports.

A retrieval and Q&A assistant for local knowledge base directories, combining grep, Read, pdfplumber, and pandas by file type for progressiv

Research what people actually say about any topic in the last 30 days, pulling posts and engagement from Reddit, X, YouTube, TikTok…

Use for any lookup, research, investigation, or question needing current info — fast and cost-effective web search via the Parallel CLI.

Diagnoses and improves Qdrant search relevance — embedding model choice, hybrid search, reranking, and measuring retrieval quality.

Build search applications with OpenSearch — index setup, semantic and vector search, hybrid search, BM25, KNN, RAG, and search quality…

Search across all connected sources in one query.

Vector search via embeddings_* (large-scale HNSW) and ruvllm_hnsw_* (WASM router for ≤11 hot patterns), with RaBitQ 1-bit quantization for…