How do you keep Pipefy automations manageable as your process grows?

What I did was use GraphQL to export every condition, automation, connection and field attribute in a Pipe.

Then I used ClaudeAI to help me create a documentation for everything.

Hello ​@Tahir Mehmood Khokhar 

Use a consistent pattern in the automation name itself, starting with a sequential ID so you can always reference it unambiguously:

[ID] [Trigger] → [Action] — [Context]
#001 Card created → Set label: Urgent — Support Request
#002 Phase moved: Review → Send email: Requester — Support Request
#003 Field updated → Move to phase: Approved — Support Request

The Depends on column referencing IDs makes the dependency map much cleaner when automations start triggering each other.

When to reorganize

Two clear signals:

• You hesitate before changing anything because you're not sure what will break
• You find yourself reading automations to understand the process instead of reading the pipe itself

At that point, reorganization is overdue. A good pipe should be self-documenting — the phases and fields tell the story, automations just enforce it.

Getting your automation data

Three ways to build this doc without doing it manually:

1. Request a report from Pipefy Support — they can export your pipe's automation configuration to a spreadsheet
2. Query via GraphQL API — pull it programmatically from the playground at developers.pipefy.com/graphql:

query {
  automations(repoId: "YOUR_PIPE_ID", organizationId: "YOUR_ORG_ID") {
    nodes {
      id
      name
      active
      conditions {
        field_id
        operation
        value
      }
      action_params {
        to_phase_id
        email_template_id
        url
      }
    }
  }
}