Zava Claims Export

Claims Report

Automate the boring part of claims reporting: take a raw export and return a

report a manager would be happy to open — headline numbers up top, breakdowns

and charts on a Dashboard, and a tidy, filterable Claims Detail table behind it.

The report design lives in the THEME block at the top of

scripts/build_report.py. That block is the reference template — colours,

fonts, and number formats. Edit it once and every future report inherits it.

When to Use

Trigger when the user has a flat claims/loss/incident export (one claim per

row) and wants it turned into a formatted, summarized report. The canonical

input is the columns below; the script tolerates minor header-name variation.

When NOT to Use

• The user wants a written narrative (memo, summary letter) → use docx.
• The user wants slides for a meeting → use pptx.
• The user wants a clickable/interactive dashboard → use canvas.
• A generic spreadsheet task with no claims structure → use xlsx.
• The export is not row-per-claim (e.g. already a pivot/summary) — reshape

it first, or fall back to xlsx.

Expected Input Schema

| Column | Example | Notes |

|--------|---------|-------|

| Claim Number | CN202504990 | Row key; blank / "Total" rows are dropped |

| Claimant Name | David King | |

| Location | 9607 Maple Dr, Bellevue, WA 98004 | City/State/ZIP parsed out |

| Damage Type | Mold damage - moderate severity; Water damage | Split into primary / severity / other |

| Status | Open - Claim is under investigation | Short status kept for grouping |

| Date Filed | 2026-04-11 | ISO or common date formats |

| Estimated Cost | 10608 | Numeric; missing values are counted, never invented |

See references/schema.md for full parsing rules and how

to add a column.

Workflow

• Find the input. If the user attached a file, use that path. Otherwise

look in input/ for the claims export (Glob input/**/*.xlsx). If nothing

is found, ask the user for the file — do not invent data.

• Build the report into scratch space (never write to output/ directly):

   python scripts/build_report.py --in "<input.xlsx>" --out working/claims_report.xlsx --title "Insurance Claims Report"

The script prints a one-line summary (`claims=… skipped_rows=…

total_cost=… avg_cost=…`) and notes any claims missing a cost. Read that

line back to the user in plain language.

• Publish to the user surface with the artifact tool (output/ is

read-only to direct writes):

   CopyArtifact(surface="output", source="working/claims_report.xlsx",
                destination="Claims Report.xlsx")

• Confirm delivery (blocking): Glob output/**/* must show the file

before you tell the user it's ready. If it's missing, re-run step 3.

• Summarize the headline numbers (total claims, total & average estimated

cost, open vs closed, top damage type) so the user gets value in the chat

even before opening the file. Ground every number in the script's output —

never estimate.

Output

A single .xlsx with two sheets:

• Dashboard — title banner (source file, generated date, filing range),

six KPI cards (Total Claims, Total / Average Est. Cost, Open, Closed,

Severe-Severity), breakdown tables by Status, Damage Type, Severity, State,

and City (each with count, % of claims, and est. cost + a totals row), and

two bar charts (claims by status, cost by damage type).

• Claims Detail — the cleaned claim table: Claim Number, Claimant, City,

State, Damage Type, Severity (colour-cued), Other Damage, Status, Date Filed,

and Est. Cost (currency-formatted), with banded rows, a frozen header, an

AutoFilter, and a grand-total row.

Guardrails

• Never fabricate data. Only values present in the source appear in the

report. Blank or "Total" rows are dropped and counted; missing costs are

reported, not filled in.

• Reconcile before reporting. The detail total and the dashboard totals both

derive from the same cleaned rows; if the printed total_cost looks wrong,

re-check the input rather than the report.

• Currency is display-only — the raw exports carry no currency code; the

$ format is cosmetic. If the user says the data isn't USD, change

THEME["money_fmt"] in the script.

• Don't hand-edit the output for one-off fixes — change the input or the

THEME/logic and re-run, so the report stays reproducible.

• Large files: the script streams values with openpyxl; for very large

exports (tens of thousands of rows) warn the user it may take a moment.