Highlights
- Heatmaps are best for rhythm and consistency
- Metric choice changes the story
- Hosted pages are easier to reuse in updates
Guide
How to build an AI activity heatmap
A practical guide to generating a GitHub-style AI coding activity heatmap with vibestats.
Intent
Guide
Focus
How to build an AI activity heatmap is a practical workflow page for turning local AI coding usage into something readable and repeatable.
Next step
Relevant commands
npx vibestats --activitynpx vibestats --activity --metric sessionsnpx vibestats --activity --share --days 365Step 1
Generate the activity view
Run `npx vibestats --activity` to create the heatmap from aggregate local usage.
Step 2
Set the metric and window
Adjust the metric or day window so the heatmap matches the question you are trying to answer.
Step 3
Publish when the view is ready
Use the share flow when you want a hosted page or image-friendly version of the result.
Why this guide exists
Most AI coding reporting problems are not about one missing command. They are about choosing the right surface: daily usage, wrapped summaries, activity heatmaps, cost views, or shareable aggregate pages.
What to expect
This guide stays focused on vibestats workflows and the pages already documented in the public command reference, so you can move from local data to a readable result quickly.
FAQ
What is the fastest way to approach how to build an ai activity heatmap?
Start with the relevant command, verify the output locally, then decide whether you need a share page, a wrapped summary, or a heatmap for communication.
Do I need to upload raw conversations for these guides?
No. vibestats works from local usage artifacts and only turns aggregate results into hosted pages when you explicitly publish them.
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