Generate text embeddings via AIMLAPI. Use for semantic search, clustering, or high-dimensional text representations with text-embedding-3-large and other mod...
Complete memory system combining Baidu Embedding auto-recall, Git-Notes structured memory, and file-based workspace search. Use when setting up comprehensive agent memory with local privacy, when you
在 Windows 上为 OpenClaw 配置本地 embedding / 本地记忆检索时使用。适用于：下载并接入 `nomic-embed-text-v1.5.Q8_0.gguf`、把 `memorySearch.provider` 改成 `local`、检查 `
Semantic memory system using Baidu Embedding-V1 for secure, local vector storage and retrieval in Clawdbot with SQLite persistence.
A Model Context Protocol server for embedded debugging with probe-rs - supports ARM Cortex-M, RISC-V debugging via J-Link, ST-Link, and more
Configure OpenClaw memory search to use Ollama as the embeddings server (OpenAI-compatible /v1/embeddings) instead of the built-in node-llama-cpp local GGUF loading. Includes interactive model selecti
模块化智能记忆系统，支持多平台 embeddings、智能重排序和 Flomo 笔记导入，实现高效语义搜索与管理。
Generate, store, and search vector embeddings with provider selection, chunking strategies, and similarity search optimization.
Expert code review for embedded/firmware projects with dual-model cross-review (Claude + Codex via ACP). Detects memory safety, interrupt hazards, RTOS pitfa...
Voyage AI embedding and reranking CLI integrated with MongoDB Atlas Vector Search. Use for: generating text embeddings, reranking search results, storing embeddings in Atlas, performing vector similar
Build and maintain a cross-platform local Zotero semantic index using metadata embeddings and PDF full-text chunk embeddings. Use when the user asks to vecto...
Create and manage modular portable database pods (SQLite + metadata + embeddings). Includes document ingestion with embeddings for semantic search. Full auto...
Automates Sovereign Local Vector Memory and Gemma-300M Embeddings. Manage local vector embeddings, model configuration, and memory health monitoring without...
Web search (embedded SearXNG), content extraction, and library docs indexing with hybrid search (FTS5 + semantic). Built-in Qwen3 embedding, no API keys required.
PostgreSQL vector database skill with pgvector extension. Enables vector similarity search, embeddings storage, RAG (Retrieval-Augmented Generation) pipeline...
Build and deploy local RAG (Retrieval-Augmented Generation) systems with offline document processing, embedding models, and vector storage.
This skill maintains the Note Embeddings for Zettelkasten, to search notes, retrieve notes, and discover connections between notes.
Manage vector storage and similarity search using TOS Vectors service. Use when working with embeddings, semantic search, RAG systems, recommendation engines, or when the user mentions vector database
Connect to Supabase for SQL queries, CRUD, table management, and vector similarity search using pgvector extension and OpenAI embeddings.
Run, tune, and troubleshoot local Ollama models with reliable API patterns, Modelfiles, embeddings, and hardware-aware deployment workflows.