Have you ever had that day where you’ve got this big scenario…
And you need to create some documentation for it before handing off to others?
Well, that day happens nearly every day. Usually, I leave such work to another system called MAke Auto-Documentation (MAAD). However, we’re testing some project management methodology changes and wanted to approach documentation differently.
So when the project manager handed me a Google Document and implied I needed to fill it in by hand, I thought to myself, “Nope.” Because much of this information is contained in Make and could be automated, I filled in the missing bits.
So, first off, we’re using Google Docs, and let’s reformat the documentation template to use template markers. Automation Documentation Template.docx (9.6 KB)
Next, let’s start building out the Make scenario by gathering and inputting information one bit at a time, like the core Make Scenario details.
We can then link it to the Google Document Template module.
Once that’s confirmed to work, we can continue filling in the rest of the details as best we can. Yet, there’s a tricky part: long-form descriptions.
And for that, thank goodness AI chatbots exist; I profess that OpenAI is my choice for generative AI needs. So with prompt magic, MAKE Scenario Analysis.md.txt (2.3 KB).
- Purpose: Clearly explain the primary goal of automation, focusing on the problem it solves and the intended benefits.
- Automation Steps: Outline the step-by-step automation workflow, including any conditions, loops, or decision points. For example:
- Step 1: Initial Action/Trigger (e.g., a user action or data entry triggers the workflow)
- Step 2: Next Action (e.g., data processing or approval flow)
- Step 3: Final Outcome (e.g., a confirmation message or report generation)
- Inputs: Specify what initiates the automation process, such as specific data, user actions, or API calls. For example, "Data entry in a CRM triggers a notification."
- Outputs: Describe the outcome or data generated by the automation. For example, "The automation generates a status update in Jira or sends an email notification."
- Dependencies: Identify any dependencies, such as other automation workflows, external systems, or integrations that this automation process relies on.
- Error Handling: Outline how errors or exceptions are managed. Include retry logic, fallback mechanisms, and any alerting strategies. For example, "In case of a failed API call, implement automatic retries with exponential backoff. If retry attempts are unsuccessful, send an alert to the admin."
And JSON response formats by Open AI module and prompt…
# RESPONSE
Output as a JSON structure.
# EXAMPLE OUTPUT
{
"Purpose": "TBD…",
"Automation Steps": "TBD…",
"Inputs": "TBD…",
"Outputs": "TBD…",
"Dependencies": "TBD…",
"Error Handling": "TBD…",
}
Suddenly, we have no more field data creation or mapping to do, and we can notify the Slack automation engineering channel about the new documentation through our completed scenario, DEV:SCENARIO:CREATE:Documentation.json (75.7 KB).
Here’s the scenario that ran on itself; DEV_SCENARIO_CREATE_Documentation Documentation.pdf (80.8 KB).
And now, the explainer video.
In the video, I mentioned prettyPrint2, a Make Enterprise Custom Function, and I’ve since replaced such with {{join}}() to be compatible with your Make organization below Enterprise.
FWIW: An example of MAAD output in Atlassian Confluence so we can easily search for Make Scenario components throughout our Make organization.
