Make sense of a messy table
Inspect a messy synthetic spreadsheet, spot missing rows and unit traps, and check whether the summary matches the numbers.
1. Scenario
Pick a work role starter with synthetic material, or switch to Bring your own.
Weekly pastry waste sheet with a missing Friday delivery
Small Business · Synthetic materialYou want to see how many croissants went unsold per day, and Friday's row has a blank delivery count.
day,delivered_croissants,sold_croissants,unsold_recorded Mon,40,36,4 Tue,40,38,2 Wed,40,35,5 Thu,40,37,3 Fri,,39,0
2. Work area
Edit the briefs or setup below before you run.
Only the header row, inferred column types, and at most 20 sample rows leave your device. The analysis function runs in your browser on all rows.
Answer and chart
Example. No model ran.Sourdough Loaves sold the most volume at 73 crates across 24 orders, and 6 invoices are currently marked unpaid.
- 1. Sum crates ordered for each product line across all 24 wholesale orders.
- 2. Count how many orders have invoice_status equal to unpaid.
- 3. List the unpaid orders so the shop owner can check the 6 rows before chasing payment.
Inspect the analyze(rows) code that ran in your browser
function analyze(rows) {
const byProduct = {};
let unpaidCount = 0;
for (const row of rows) {
const prod = String(row.product || "Other");
const crates = Number(row.crates) || 0;
if (!byProduct[prod]) {
byProduct[prod] = { product: prod, orders: 0, totalCrates: 0 };
}
byProduct[prod].orders += 1;
byProduct[prod].totalCrates += crates;
if (String(row.invoice_status) === "unpaid") {
unpaidCount += 1;
}
}
const table = Object.values(byProduct).sort((a, b) => b.totalCrates - a.totalCrates);
const chart = table.map((p) => ({ label: p.product, value: p.totalCrates }));
const top = table[0] || { product: "None", totalCrates: 0 };
return {
answer: top.product + " sold the most volume at " + top.totalCrates + " crates across " + rows.length + " orders, and " + unpaidCount + " invoices are currently marked unpaid.",
table,
chart,
checkOne: {
label: "Orders with unpaid invoices",
figure: unpaidCount,
column: "invoice_status",
equals: "unpaid",
mode: "count"
}
};
}Check one number by hand
Reported: 6 · Rows found: 6Orders with unpaid invoices: Filter where invoice_status equals unpaid. Below are all 6 matching rows from the 24-row spreadsheet so you can count or sum them yourself.
3. Run
Nothing leaves your browser until you press Run.
Sends only the column header and at most twenty sample rows when you press run. to job data_code (claude-sonnet-5-5, effort medium). Raw text is processed in memory and not stored.
4. Inspect
See what left the browser, which model ran, and the receipt.
Nothing sent yet. When you run, only headers and at most 20 sample rows leave this device.
All 24 rows stay in your browser and run inside the sandboxed Web Worker.
data_code · claude-sonnet-5-5 (effort medium, max 1600 tokens). Haiku reads the schema and sample rows to propose checks you can verify against the full table.
0 runs used · source: offline · Example. No model ran.
5. Judge
Did the summary flag Friday's blank `delivered_croissants` value instead of treating Friday's 0 as verified?
50 is a coin flip. 99 is certain. Honest confidence scores best.
6. Debrief and Keep
What to check next time, the matching lesson, and keeping this setup as a recipe.
What to check next time
Blank cells often turn into zeros in downstream summaries. Separating the four complete days (Mon to Thu = 14 unsold) from Friday's missing delivery cell keeps your ordering math accurate.
Keep as a recipe
Save the stronger brief and scenario setup to your device so you can reuse or adapt it in Keep.