Results for “llm-agents”

25 skills
More results
antigravity
AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines with observability and security.
42.4k
mukul975
Orchestrating LLM Attacks With Pyrit
Automate multi-turn adversarial conversations against LLM agents using Microsoft PyRIT, including Crescendo and Tree-of-Attacks-with-Pruning (TAP) attack chains with scorer feedback loops.
24.6k · bundle
johnalbertini14-glitch
Mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
1 · bundle
nimoqup046-collab
AI Ml
Orchestrates AI/ML development workflows covering LLM applications, RAG systems, AI agents, ML pipelines, and observability.
2
rootcastleco
AI Engineer
Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.
6
agentskillexchange
Llamaindex Agent
Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.
28
orchestra-research
Langchain
Build LLM-powered applications with agents, chains, and RAG using a framework that supports multiple providers and 500+ integrations.
10.4k · bundle
tools-only
007 File 265f6921
Converts documentation websites, GitHub repositories, and PDF files into AI-ready skills for multiple LLM platforms.
7 · bundle
cloudflare
Agents Sdk
Build AI agents on Cloudflare Workers using the Agents SDK, covering stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, and browser automation.
2.1k · bundle
muratcankoylan
Project Development
Guides project-level decisions for LLM-powered systems: task-model fit, pipeline architecture, token and cost estimation, and agent-assisted iteration.
16.9k · bundle
lingxling
AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
253
demerzels-lab
Moa
Orchestrates three frontier models to debate a question and synthesizes their best insights into a single superior answer.
10 · bundle
antigravity
AI Engineer
Build production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search, multimodal AI, and enterprise integrations.
42.4k
jorcan
AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
0 · bundle
phoroth
AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
3
lucaspmarie-a11y
AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
5
nimoqup046-collab
Daily
Reference for building real-time voice and multimodal AI agents with Pipecat, covering pipelines, speech services, LLMs, transports, and deployment.
2
jorcan
Daily
Provides a reference for building real-time voice and multimodal AI agents with Pipecat, covering pipeline architecture, speech services, LLM integration, transports, and deployment.
0 · bundle
johnalbertini14-glitch
Moa
Runs a Node.js CLI that sends a question to three frontier LLMs in parallel, then synthesizes their responses into a single answer via an aggregator model, with paid and free tiers.
1 · bundle