Question 1

What is Skyway?

Accepted Answer

Skyway is a workflow orchestration platform for developer teams. You define automation pipelines as .sky workflow files — specifying which AI models to use, what GitHub events to listen for, what data to fetch, and how to handle the outputs. Skyway runs those workflows, tracks their execution, and gives your team full visibility into every run.

Question 2

What is the .sky workflow language?

Accepted Answer

The .sky DSL uses Unicode-delimited sections to organize workflow logic into distinct concerns. A meta block defines the workflow name, trigger events (e.g. a GitHub issues.labeled event), required secrets, and output style. Each subsequent block is either a node config block (HTTP fetch, model selection, effort level, dependencies) or a prompt block (the instruction text sent to the AI model). Workflows are plain text .sky files stored in .sky/workflows/*.sky in your repository — version-controllable, auditable, and readable as code.

Question 3

Does Skyway support GitHub integration?

Accepted Answer

Yes. Skyway supports GitHub trigger integration, meaning workflows can be triggered automatically by GitHub events such as issues.labeled. Workflows are stored as .sky files in your repository, making them version-controllable and auditable alongside your codebase.

Question 4

What monitoring does Skyway provide?

Accepted Answer

Skyway surfaces full run histories, audit logs for every action taken by the system, integration health dashboards, and spend tracking per workflow and team. This gives teams the confidence to run AI automation in production without sacrificing oversight.