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This project is a skill integration that connects external applications to NotebookLM for source-grounded document querying and knowledge base retrieval. It functions as a tool for retrieving answers based on specific source material stored within a remote notebook service.
The main features of pleaseprompto/notebooklm-skill are: Document Grounding, External Knowledge Integrators, Knowledge Base Management, Knowledge Base Link Organizers, Notebook-Based Organization, External Service Integrations, Google Account Authenticators, Google Account Integrations.
Projects with overlapping indexed features include: anthropics/skills — This project provides a standardized framework for extending the functional range of artificial intelligence agents… livekit/agents — This project is a framework for developing multimodal AI agents that function as programmable participants in… addyosmani/agent-skills — Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding… fetchai/innovation-lab-examples — This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a… nocobase/nocobase — This platform is a modular, metadata-driven framework designed for building custom business applications and data… livekit/livekit — LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with…
This project provides a standardized framework for extending the functional range of artificial intelligence agents through a registry of modular, declarative instructions. It enables agentic workflow automation by allowing developers to define task-specific behaviors and operational constraints that guide how agents interact with external tools and execute multi-step processes. The system distinguishes itself through a directory-based discovery model and a plugin-registry architecture that facilitates the distribution of specialized workflows. By utilizing a schema-driven specification that
This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu
Agent-skills is a collection of structured instructions and behavioral personas designed to standardize how AI coding agents perform engineering tasks. It functions as a workflow orchestrator that maps natural language intent to repeatable technical sequences and verification checklists. The project distinguishes itself through the use of specialized markdown-defined roles, such as security auditors or test engineers, to apply targeted domain expertise. It employs an evidence-based verification model that requires runtime data or passing tests as mandatory exit criteria to ensure AI-generated
This project provides a comprehensive framework for building, deploying, and orchestrating autonomous agents within a decentralized network. It serves as a collection of patterns and examples for developing intelligent software entities capable of performing complex tasks, making decisions, and interacting with other agents to achieve shared goals. The framework distinguishes itself through its focus on multi-agent orchestration and decentralized communication. It enables the coordination of specialized agent teams that collaborate on workflows through structured messaging protocols, allowing