Google Analytics holds the numbers, but nobody logs in daily, so trends slip past unnoticed. This digest brings the summary to where the team already works.
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README.md
Why this subagent
Google Analytics holds the numbers, but nobody logs in daily, so trends slip past unnoticed. This digest brings the summary to where the team already works.
Each day it pulls sessions, top pages, and conversions, compares them to the prior period, and writes a short note on what actually moved. The metrics and the note land as a dated row in Baserow, building a running history you can scroll instead of rebuilding reports each week.
How it runs
Used at step 01 to kick off the pipeline.
Write
Used at step 01 to kick off the pipeline.
WebFetch
Used at step 01 to kick off the pipeline.
WebSearch
Used at step 01 to kick off the pipeline.
Compare each metric against the prior period to mark what rose and what fell.
pending
Write a short note explaining the most notable movement in plain language.
pending
Append the metrics and the note as a new dated row in the Baserow table.
pending
Sample output
json
// Sample output
// (generated when the pipeline finishes)
Pull daily Google Analytics metrics, compare to the prior period, and append them to Baserow with a plain-language note.
Unlock the rest
The full agent definition, install snippet, and starter task are gated for community members.
Members get the full `.md` agent file, the npm / pnpm install one-liners, a starter prompt that we've tuned against real runs, and the open-source repo when this automation ships there. One email, magic link, done.