Best AI Agent Frameworks for Linear

Eve serves as a framework for creating agents, akin to how Next.js functions for web applications, offering a specialized environment for agent development. It employs Markdown to articulate instructions and skills, while TypeScript is utilized for implementing tools, ensuring durable execution by default. An agent is essentially a directory that outlines its instructions and skills using Markdown, defines tools through TypeScript, and facilitates deployment. Eve meticulously compiles this directory, orchestrates durable workflows, and integrates various channels, providing developers with a systematic approach to construct production-ready agents without the need to piece together disparate solutions. An instructions.md file can represent a fully functional agent, and the agent.ts file empowers teams to select a model or adjust the runtime configuration. Skills can be reused as Markdown playbooks that are loaded when needed, allowing the agent to receive targeted guidance without the burden of carrying unnecessary information in every prompt. Tools are introduced as TypeScript files, with their filenames serving as the tool names, eliminating the requirement for any registration process. Each agent operates within its own isolated sandbox and includes file tools, and there is also the option for custom sandbox configurations, enhancing flexibility for developers. This robust framework not only streamlines agent creation but also fosters innovation by allowing developers to focus on building unique functionalities.

Eve serves as an open-source framework for developing AI agents that you fully control, structured around a file system and equipped with a runtime suitable for production use. Defining an agent is as straightforward as creating an instructions.md file, while additional components like model configurations, skills, tools, sandboxes, channels, connections, subagents, schedules, and evaluations can be incorporated as the agent evolves. Tools can easily be established by placing TypeScript files into the designated tools directory, and skills are formulated as Markdown playbooks that activate only when needed. These agents have the capability to integrate with platforms such as GitHub, Stripe, and Linear via secure authenticated connections, and they can interact through various channels like Slack, Discord, Teams, web chats, APIs, cron jobs, command-line interfaces, and tailored applications—all originating from the same codebase. Moreover, specialized subagents are capable of managing delegated tasks, utilizing their own unique prompts, tools, and sandboxes, enhancing the overall functionality and adaptability of the agent. This versatility allows developers to customize their AI systems to fit a wide range of applications and use cases.