Reusable agent-native
validation workflows
From prompt to reusable validation in four steps
“We basically stopped creating full preview environments and replaced our custom solution with Signadot. The strategy using routing keys is much lighter, and we are able to provide an isolated environment, even with isolated databases, per PR quite fast.”
Validation that keeps up with agent-speed development.
Bitso scaled branch-based development for 250+ engineers and 200+ microservices on Signadot, with coding agents validating changes the same way.
Two skills close the loop for coding agents
Governed by platform teams, used by everyone
Validate against your real system before the PR opens
Ship working, agent-generated code at scale with lightning-fast, deterministic validation that runs before the PR opens.
Plans FAQ
What is a Signadot Plan?
A Plan is a small, reusable validation workflow. It is authored from a natural language prompt, compiled into a sequence of typed action invocations, and stored as a versioned artifact that developers and coding agents invoke by name. Running a plan validates a change end to end against live services in a Sandbox.
What are Actions?
Actions are the typed, deterministic building blocks Plans are composed from. The catalog includes actions like request-http for API checks, playwright for browser flows, and k6 for load scenarios. Each action is defined in markdown with declared inputs and outputs, checked into a git repo your platform team controls, and synced into the action registry.
How do coding agents use Plans?
Through two agent skills. The signadot-plan skill authors a new plan from a prompt, tags it, and gives it a selection hint. The signadot-validate skill reads a code diff, picks the matching plan by its selection hint, runs it in a Sandbox against real services, and iterates on failures until the change passes. Both work with the Signadot MCP server or fall back to the CLI.
Where do Plans execute?
Plan steps run in isolated, rootless execution environments on Plan Runner Group pods inside your Kubernetes cluster. The control plane compiles and schedules the plan, resolves parameters and secrets, and collects outputs and artifacts, while the validation traffic itself stays on your cluster.