LLM-Agent provides a structured architecture for building intelligent agents using LLMs. It includes a toolkit for defining custom tools, memory modules for context preservation, and executors that orchestrate complex chains of actions. Agents can call APIs, run local processes, query databases, and manage conversational state. Prompt templates and plugin hooks allow fine-tuning of agent behavior. Designed for extensibility, LLM-Agent supports adding new tool interfaces, custom evaluators, and dynamic routing of tasks, enabling automated research, data analysis, code generation, and more.

SquadflowAI Studio allows users to visually compose AI agents by defining roles, tasks, and inter-agent communications. Agents can be chained to handle complex multi-step processes—querying databases or APIs, performing actions, and passing context among one another. The platform supports plugin extensions, real-time debugging, and step-by-step logs. Developers configure prompts, manage memory states, and set conditional logic without boilerplate code. Models from OpenAI, Anthropic, and local LLMs are supported. Teams can deploy workflows via REST or WebSocket endpoints, monitor performance metrics, and adjust agent behaviors through a centralized dashboard.

Anti-Agent-Agent provides a programmable framework to generate both adversarial and defensive AI agents for conversational models. It automates prompt crafting, scenario simulation, and vulnerability scanning, producing detailed security reports and metrics. The toolkit supports integration with popular LLM providers like OpenAI and local model runtimes. Developers can define custom prompt templates, control agent roles, and schedule periodic tests. The framework logs each interaction, highlights potential weaknesses, and recommends remediation steps to strengthen AI agent defenses, offering an end-to-end solution for adversarial testing and resilience evaluation in chatbot and virtual assistant deployments.

Promptsio is a comprehensive library featuring over 100 AI prompts specifically designed for OpenAI’s Chat-GPT. This platform aims to streamline the process of prompt engineering by providing ready-to-use prompts that cater to various applications. Whether you’re a developer, marketer, or just a curious individual, Promptsio helps you generate effective prompts for better AI interactions, enhancing productivity and creativity.

SwiftAgent offers a robust toolkit for constructing intelligent agents by integrating OpenAI's models directly in Swift. Developers can declare custom actions and external tools, which agents invoke based on user queries. The framework maintains conversational memory, enabling agents to reference past interactions. It supports prompt templating and dynamic context injection, facilitating multi-turn dialogues and decision logic. SwiftAgent's async API works seamlessly with Swift concurrency, making it ideal for iOS, macOS, or server-side environments. By abstracting model calls, memory storage, and pipeline orchestration, SwiftAgent empowers teams to prototype and deploy conversational assistants, chatbots, or automation agents quickly within Swift projects.