Building Your First Optimizely Opal Custom Tool (www.33sticks.com)

Optimizely published a step-by-step tutorial showing how to build, deploy, and register a custom Opal tool so your Opal AI agents can call your own services. The walkthrough builds a simple "greeting" tool in Python (requires Python 3.12+), using the Opal Tools SDK (imported as opal_tools_sdk), FastAPI and uvicorn. Key pieces: ToolsService auto-creates the /discovery endpoint Opal uses to discover tools, @tool registers your callable, and Pydantic BaseModel defines validated parameters. You can test locally via /discovery and POST /tools/greet_user, then deploy to Railway (runtime.txt + Procfile) to get a public URL to register in Opal. Once registered, create a specialized agent that enables the tool and add instructions in the agent prompt so Opal knows when to call it. This matters because custom tools let teams extend Opal with domain-specific connectors, secure APIs, and richer workflows. Important technical notes and gotchas: the SDK requires Python 3.12+; Optimizely won’t auto-detect tool changes—you must manually click “Sync” after redeploys; ensure discovery is reachable and the Procfile is in the repo root. Best practices include clear tool names/descriptions, Pydantic validation, helpful error responses, versioning tools for migrations, and adding auth or interactive IslandResponse UI elements as you scale.