Spellcaster provides a structured approach to building AI Agents by using 'spells'—a combination of prompts, logic, and workflows. Developers write YAML configurations to define agents’ roles, inputs, outputs, and orchestration steps. The CLI tool executes spells, routes messages, and integrates seamlessly with OpenAI, Anthropic, and other LLM APIs. Spellcaster tracks execution logs, retains conversation context, and supports custom plugins for pre- and post-processing. Its debugging interface visualizes the sequence of calls and data flows, making it easier to identify prompt failures and performance issues. By abstracting complex orchestration patterns and standardizing prompt templates, Spellcaster reduces development overhead and ensures consistent agent behavior across environments.