4 posts tagged with "customization"

The Toolpack SDK workflow engine is powerful out of the box, but its real strength emerges when you customize it. Instead of relying solely on the built-in AGENT_WORKFLOW, CODING_WORKFLOW, or CHAT_WORKFLOW presets, you can craft workflows that match your exact requirements—whether that's a research agent, a code reviewer, or a deployment orchestrator.

This guide shows you how to build custom workflows from scratch, tune planning behavior, control step execution, and design workflows that fit your specific use cases.

Toolpack SDK ships with a lot of built-in tools across categories like file system, web, databases, Git, and code analysis. But every project has unique needs - internal APIs, proprietary systems, domain-specific operations. Custom tools let you extend your AI agent's capabilities without limits.

This guide shows you exactly how to build custom tools, based on real production implementations from the Toolpack CLI project.

By default, the Toolpack SDK provides a unified AI agent runtime with full access to an extensive toolset. But giving an AI full runtime access is not always the correct architectural choice. Sometimes you need a chat-only assistant, a read-only DevOps reviewer, or a highly specialized agent confined to a strict workflow.

This is exactly what Modes solve. A "Mode" shapes the AI's persona, its capabilities, and its operational boundaries. In this guide, we will explore what modes do, how the built-in modes work, and how to create powerful custom ones from scratch.

Toolpack SDK ships with built-in support for OpenAI, Anthropic, Gemini, and Ollama. But sometimes you need to integrate a different provider -- xAI's Grok, Groq, DeepSeek, Azure OpenAI, or your company's own model. Custom providers make that possible without giving up any SDK features like tool calling, streaming, or embeddings.

This guide walks through exactly how to build one, based on the real xAI adapter used in the Toolpack CLI project.