Shopify Daily Sales Digest with OpenCode
One run a morning, thirty a month, and every one does the same modest thing: read yesterday, read the day before, write four sections. OpenCode lets you pick the model underneath, so a job that is mostly counting and formatting does not have to be paid for at reasoning prices. If a digest starts reading thin, you move the model up and leave the rest of the agent alone.
Watch it work before it's live
Run a staged conversation — no account needed. The agent handles it for real while a simulated world answers its tool calls; nothing touches real accounts, and nothing is actually sent.
Morning tick, Monday 08:00
The 08:00 tick fires. Yesterday the store took 214 orders worth 18,940 EUR against 176 orders worth 15,220 EUR on Saturday, and 63 of yesterday's buyers were new. The largest single order is 1,180 EUR of wholesale ceramic drippers to a cafe in Lyon, and three orders placed from the same Rotterdam address were cancelled within an hour.
Set up in minutes
Using this template drops you into a guided setup. It asks exactly this, nothing else:
Connect Shopify
One sign-in. The agent acts through your account, scoped to what this template uses.
Connect Slack
One sign-in. The agent acts through your account, scoped to what this template uses.
Store context
What your store sells and what a normal day looks like, in your own words: main products, typical daily order count and average order value, your currency, and anything seasonal. The agent uses this only to tell an ordinary morning from an odd one, never as a source of numbers.
Digest style
The exact sections you want in the message and the order you want them in, how much detail each gets, your date format, and whether you want plain numbers or a line of commentary with them.
Runs on OpenCode
Preselected for this page — connect your OpenCode account during setup, or switch to NoClick's built-in models with one click.
Watch it handle a test run
A staged conversation against a simulated world — then it’s live.
Why OpenCode for this agent
Pay for what it is
Copying figures out of Shopify responses is retrieval rather than analysis. A model-agnostic harness turns that into a budget decision instead of a fixed cost.
One field to change
Testing a cheaper model against the same staged mornings takes a minute and touches nothing else in the workflow.
Before you fork
Does a smaller model still follow the no-estimating rule?
That is the rule to check first when you drop model size, because rounding for effect and stating an uncalculated percentage are exactly what a weaker model reaches for under a formatting instruction. Half The Numbers Missing is built for this: the correct output names the missing figure and says the totals are incomplete. If a model papers over that gap, step back up one.
Run it with a different agent
Put Shopify Daily Sales Digest to work on OpenCode
Free to start. Guided setup, a test run against staged conversations, and it's live.