- Comience ya
- Mejores prácticas
- Capacidades
- Aptitudes
- CLI
- Ejemplos
- Resumen de ejemplos
- Receta: crear un agente
- Receta: automatizar con RPA
- Receta: introducir datos en una aplicación web
- Receta: extraer datos de una aplicación de escritorio
- Receta: refactorizar y probar un flujo de trabajo
- Receta: un proceso basado en colas con REFramework
- Receta: crear un Maestro Flow
- Recipe: build a Maestro Case
- Receta: aplicación codificada y flujo de trabajo de API
- Recipe: build a coded function
- Receta: extraer datos de documentos con IXP
- Avanzado
- Ayuda
Build, test, and publish a coded function that normalizes an order payload, using a coding agent.
This recipe builds a coded function that normalizes an order payload — trimming whitespace, standardizing IDs, and converting dates to a consistent format. It shows the full loop from your prompt to a function you can call from an automation.
Requisitos previos
- La CLI
uipy las habilidades instaladas, y una sesión autenticada (consulta Instalación y configuración). - An empty working folder, or an existing project you want to add the function to.
Build the function
-
Open your coding agent in your working folder.
-
Describe the transform:
"Create a coded function that normalizes this order payload: trim whitespace from every string field, uppercase the order ID, and convert the order date to ISO 8601. Here's a sample payload: [paste sample JSON]."
-
Review the function the agent scaffolds — the input and output contract, and the transform logic.
-
Ask the agent to run the function locally against your sample payload and a second, malformed one, to see how it handles bad input.
-
Ask the agent to publish the function once it behaves as expected.
Resultado
A published coded function that normalizes an order payload, ready to be called from a Maestro service task, an agent, or a workflow.
Próximos pasos
Wire the function into the automation that needs it — for example, a Maestro Flow that calls it before routing the order for approval. See Coded functions.
The generated contract and file layout depend on your agent, your prompt, and whether you chose Python or TypeScript/JavaScript. Use the transform's correctness against your sample payloads, not the exact files, as your signal of success.