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agentmark

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Basic Information

AgentMark is a developer-focused toolkit and markup format for authoring, testing, and evaluating AI agents and prompts. It combines familiar Markdown syntax with JSX-like components so developers can express prompts, logic, and agent workflows in a readable file format. The repo targets TypeScript and JavaScript projects with planned Python support, and focuses on integrating prompts with model SDKs via adapters rather than directly implementing model calls. AgentMark provides CLI tools to initialize projects and run .prompt.mdx prompt files for rapid iteration. The project aims to make prompt engineering more reliable by offering unified prompt configuration, type safety, and tooling that works across multiple model providers and output types, enabling developers to build multi-step, agentic behaviors without depending on provider-specific structured output features.

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App URL
https://github.com/agentmark-ai/agentmark
Github Repository
https://github.com/agentmark-ai/agentmark/blob/main/README.md

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App Details

Features
AgentMark includes multimodal generation support so a single prompt file can request text, structured objects, images, and speech. It provides primitives for tools and agentic workflows that enable API calls, calculations, and multi-step reasoning. The system supports file attachments for image or document inputs and offers type safety via JSON Schema and auto-generated TypeScript types. Prompts can include conditionals, loops, props, and filter functions using JSX-like syntax. A CLI is provided to run and debug prompts locally. Adapters let AgentMark format prompt inputs for different SDKs; built-in adapters include a Vercel recommendation, a default raw JSON adapter, and a custom adapter option, with additional adapters planned. The repo also emphasizes unified prompt configuration and syntax highlighting to speed development.
Use Cases
AgentMark helps developers accelerate prompt and agent development by providing a structured, reusable format for prompts and built-in tooling for testing and evaluation. Type safety and JSON Schema reduce runtime errors and improve reliability of inputs and outputs. The CLI enables fast local iteration and debugging of .prompt.mdx files. Adapter-based integration allows teams to connect prompts to their preferred SDKs without changing prompt source files, reducing vendor lock-in. Support for multimodal outputs and file attachments makes it practical to build image analysis, document processing, and speech-enabled workflows. Conditionals, loops, and tool integrations let developers express complex agent logic and multi-step flows in a maintainable way, improving reproducibility and evaluation of agent behavior.

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