Arazzo is solving the right problem for AI tools. The spec just isn't there yet.

Arazzo, an OpenAPI Initiative specification for documenting multi-step API workflows, has gained renewed relevance as AI agents increasingly orchestrate APIs through MCP servers, tools, CLIs, and direct calls, where unreliable API-chain inference can cause hallucinations, latency, and high token costs. Although Arazzo was initially less compelling for human-facing API documentation and explorers, it became more useful for agentic execution, yet the author identifies limitations in its two-layer conditional logic, mixed runtime-expression syntaxes, inability to transform filtered outputs effectively, lack of current human-in-the-loop elicitation support, and potential drift caused by separate OpenAPI and workflow files. To address these gaps, the author’s team created Flower, an open-source internal workflow model that can import Arazzo documents and offers simplified step conditions, dot notation with JMESPath-based transformations, and self-contained workflows without OpenAPI dependencies. Despite Flower’s growing use among clients, the author views it as an interim alternative and hopes future Arazzo versions mature into a broadly adopted standard for reliable AI-driven API workflows.

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