xlsx-financial-report

name: xlsx-financial-report description: | Generate a native Excel (.xlsx) file styled as a clean financial / KPI / dashboard report. Use when the user asks for an "Excel report", "financial report", "KPI dashboard", "monthly report", ".xlsx", or similar tabular deliverable where the output must look professional (not just raw data). Output is a single .xlsx file produced via openpyxl through the execute_python_code tool. Output opens cleanly in Excel / Google Sheets / Numbers. Do NOT use this skill for ad-hoc data exploration or raw CSV dumps — use the regular excel tool for those. when_to_use: | When the user wants a polished financial / KPI / dashboard Excel deliverable (xlsx) where the file is meant to be opened and skimmed — not raw data dumps. Use the regular excel tool instead for ad-hoc exploration / CSV-style output. tags: - xlsx - excel - financial - report - dashboard

Editorial Financial Report (.xlsx)

You will generate one .xlsx file via openpyxl by writing a Python program and running it through the execute_python_code tool. Save to the workspace, then report the path + a 1-line content summary.

📦 Required runtime packages

The sandboxed execute_python_code ships with pandas, numpy, matplotlib, and openpyxl>=3.1.0 preinstalled — no extra installation step is needed. Just import openpyxl at the top of your script and proceed.

Note: execute_python_code accepts only code and capture_output arguments; there is no packages parameter. All required libraries are already available in the sandbox image.

💾 How to save the file

execute_python_code already runs with the task's output directory as the current working directory. Save the workbook with a plain filename (no path), e.g.:

wb.save("xagent_metrics_dashboard.xlsx")   # ✅ correct

Do NOT use:

• wb.save("/workspace/foo.xlsx") — /workspace does not exist on this host
• wb.save("output/foo.xlsx") — there is no nested output/ subdir
• BytesIO + base64 round-trips — just save to disk directly.

Verify with os.path.getsize("xagent_metrics_dashboard.xlsx") before declaring success. A real openpyxl-generated xlsx is always >5 KB — if your saved file is under 1 KB it's broken or empty.

🔗 Make it clickable in chat — REQUIRED

The Python executor returns a markdown_link field in its response for every workspace file it generated (or a file_refs[] array with one entry per file). Read the tool's response and use the returned markdown_link string verbatim. In your final answer, the first line MUST be that chip link itself — bare markdown, NOT inside backticks, NOT presented as "file_id: UUID":

✅ CORRECT (renders as clickable chip — chat UI looks for this exact pattern):

[xagent_metrics_dashboard.xlsx](file:20fae785-3823-4906-b385-d0e8a7807dc8)

The UUID comes from the executor response. Do not fabricate one.

❌ WRONG — common failure that renders as plain text:

已生成报表:
- 文件名: `xagent_metrics_dashboard.xlsx`
- file_id: `20fae785-3823-4906-b385-d0e8a7807dc8`

❌ ALSO WRONG — chip link inside a code fence: ```[name](file:UUID)``` suppresses markdown so the link won't render as a chip.

❌ ALSO WRONG — calling get_file_info(...) to "fetch" the file_id. Its FileInfo return shape does not include file_id; the chip reference is already on the executor result.

Plain-text mention of the filename is not clickable — the user must navigate to File Management to find it. Always lead with the bare [name](file:UUID) line, then describe the contents.

⚠️ Hard rules — NO exceptions

0. MATCH THE USER'S LANGUAGE. If the prompt is Chinese (中文), ALL workbook text (title, subtitle, section banners, KPI labels, table headers, deltas) must be in Chinese. Translate template phrases like SUMMARY → 汇总, DETAIL → 明细, As of YYYY-MM-DD → 截至 YYYY-MM-DD. Numbers and date formats stay locale-neutral.

1. One accent color only. Pick one of the 5 palettes below; use only its 4 hex values (ink, paper, paper_tint, accent). paper_tint is the alternating-row band shade — without it you can only do flat one-color rows. No other colors anywhere. In code, define a palette = {"ink": "...", "paper": "...", "paper_tint": "...", "accent": "..."} dict ONCE at the top of the script and reference palette["ink"] / palette["accent"] / palette["paper_tint"] / palette["paper"] everywhere — do not copy literal hex values into individual styling calls.

2. Two fonts only. Headers / titles = Cambria (serif, Office native). Body / data = Calibri (sans, Office default).

3. Forbidden:

   • 3-D charts, donut/pie charts with > 5 slices, exploded pies
   • rainbow chart palettes (color charts only with ink + accent)
   • chart shadows, glow, bevel, gradient fills
   • thick borders (use thin only, sparingly)
   • merged-cell abuse (merge only for section banners across columns)
   • emoji as decoration
   • Comic Sans, Arial Black, MS Sans Serif
   • rainbow conditional formatting (only monochrome data bars / 2-stop min→max scale in ink shade)

4. Real data only. No fabricated numbers. If the user didn't provide data, ask first — don't invent.

5. Always include: title row, frozen header pane, alternating row bands using paper-tint, summary KPI block at top.

6. Failure honesty — NEVER fake the deliverable.

   • If execute_python_code raises after multiple retries, STOP and report the actual error to the user. Do not write a stub file like write_file("report.xlsx", "placeholder") to make the chip appear.
   • The final answer must reflect what was actually written. Do not describe KPI values, deltas, or sections that aren't in the saved .xlsx. If the chart didn't render, say so — don't claim it did.
   • It is better to deliver a chart-less but real .xlsx (drop the chart block and save without it) than to fabricate a success report. If the chart code keeps failing, ship the workbook without the chart and tell the user the chart was omitted.

🎨 Palettes — pick ONE

Each: ink (text + borders + chart series), paper (workbook bg / cells), paper-tint (alternating row band), accent (single highlight color for KPI values / chart series 2 / positive deltas).

• Bloomberg Mono (default / fintech) ink 1A1A1A · paper FFFFFF · paper-tint F7F7F5 · accent D97706
• Indigo Sheet (corporate / SaaS) ink 0F172A · paper FFFFFF · paper-tint F1F5F9 · accent 4F46E5
• Forest Ledger (sustainability / impact) ink 1A2E1F · paper FAFAF7 · paper-tint F0EDE3 · accent 059669
• Crimson Quarterly (executive / board) ink 1F1F1F · paper FFFFFF · paper-tint F5F2EE · accent B91C1C
• Slate Audit (compliance / audit) ink 0F1419 · paper FCFCFC · paper-tint F0F2F4 · accent 0891B2

✒️ Typography rules (openpyxl Font sizes in pt)

• Title (A1, merged across cols): Cambria, 22pt, ink, bold
• Subtitle / date (A2): Calibri, 11pt, ink, italic
• Section header (banner row): Calibri, 12pt, paper bg + ink color, bold, merged across the section's columns
• Table header: Calibri, 11pt, ink bg + paper color, bold (thin bottom border)
• Data: Calibri, 10pt, ink color
• KPI big number: Cambria, 24pt, ink, bold
• KPI label: Calibri, 9pt, ink-with-50%-opacity (or just slightly lighter), uppercase

🏗️ Standard layout

A1: [merged] Report Title (22pt Cambria bold)
A2: Subtitle / period · As of YYYY-MM-DD (11pt Calibri italic)
A3: (blank, 6pt row height for breathing room)

A4: [section banner] "SUMMARY"  (banner row, merged)
A5-D5: KPI cards row — each KPI in a 1×2 cell block
  - Row 5: KPI label (small caps)
  - Row 6: KPI big number (24pt Cambria)
  - Row 7: delta vs previous period (Calibri 10pt, accent if positive, ink-50 if negative)

A9: (blank)
A10: [section banner] "DETAIL"
A11: Table header (frozen at row 12)
A12+: Data rows with alternating paper-tint

📊 Number formatting (Excel format codes)

💱 Currency default — pick carefully

The user's name / locale is NOT a reliable signal for which currency the report's subject company uses. Pick currency by the subject domain, not by who's asking:

• Default → USD ($) for: SaaS, B2B software, fintech, US/global companies, crypto, VC metrics (ARR / MRR / NRR / CAC / LTV are industry-standard USD).
• Use CNY (¥) only when: the user explicitly says CNY/RMB, the company is named as Chinese (e.g. Alibaba / Pinduoduo / ByteDance), or the data source is a Chinese filing.
• Use EUR (€) for EU-based companies explicitly mentioned.
• Use GBP (£) for UK-based companies explicitly mentioned.

When in doubt, default to USD and note the assumption in cell A2 subtitle (e.g. Q1 2026 Quarterly Review · As of 2026-03-31 · USD).

📈 Chart styling (openpyxl charts)

• Chart types allowed: LineChart, BarChart (type="col", never 3-D), ScatterChart. NEVER import BarChart3D, PieChart3D, etc.
• Series colors: only ink and accent (max 2 series). For more, use line variations (solid vs dashed) in ink.
• No legend if only 1 series. If 2 series, legend at right, no border, no fill.
• No axis title unless absolutely necessary. Axis labels font: Calibri 9pt.
• Chart border: none. Chart background: paper.
• Title: 12pt Calibri bold, ink, left-aligned above chart.

⚠️ openpyxl 3.x chart API gotchas — copy this verbatim, don't improvise

The openpyxl chart API is full of footguns. Use ONLY the imports below and ONLY the kwargs shown. Most common mistakes:

✅ Tested line-chart snippet (openpyxl 3.x — copy as-is)

Before the snippet: define your chosen palette once. Example for Indigo Sheet:

palette = {"ink": "0F172A", "paper": "FFFFFF",
           "paper_tint": "F1F5F9", "accent": "4F46E5"}

Reference palette["ink"] / palette["accent"] / palette["paper_tint"] in the styling code below instead of copying hex literals.

from openpyxl.chart import LineChart, Reference
from openpyxl.chart.label import DataLabelList
from openpyxl.chart.marker import Marker
from openpyxl.chart.shapes import GraphicalProperties
from openpyxl.chart.axis import ChartLines
from openpyxl.drawing.line import LineProperties

# Assume helper columns H (categories) and I (values) at rows 11..14
ch = LineChart()
ch.title = "Monthly Agent Runs (Jan–Apr 2026)"
ch.width, ch.height = 20, 10
ch.legend = None  # 1-series chart -> no legend

vals = Reference(ws, min_col=9, min_row=11, max_row=14)  # column I
cats = Reference(ws, min_col=8, min_row=11, max_row=14)  # column H
ch.add_data(vals, titles_from_data=False)
ch.set_categories(cats)

# Series styling — kwarg is `ln=`, not `line=`. `w` is in EMU (12700 EMU = 1pt).
s = ch.series[0]
s.graphicalProperties = GraphicalProperties(
    ln=LineProperties(solidFill=palette["ink"], w=25000)  # ~2pt
)
s.marker = Marker(symbol="circle", size=7)
s.marker.graphicalProperties = GraphicalProperties(solidFill=palette["accent"])

# Data labels (optional)
s.dLbls = DataLabelList(showVal=True)
s.dLbls.numFmt = '#,##0'

# Value-axis gridlines — must wrap in ChartLines(spPr=...). The
# gridline tint comes from the palette's paper_tint, not a hard-coded
# grey.
ch.y_axis.majorGridlines = ChartLines(
    spPr=GraphicalProperties(ln=LineProperties(solidFill=palette["paper_tint"], w=6350))
)
# No category-axis gridlines
ch.x_axis.majorGridlines = None

# Backgrounds (optional — paper is usually already default)
ch.plot_area.graphicalProperties = GraphicalProperties(solidFill=palette["paper"])

ws.add_chart(ch, "A22")

✅ Tested bar-chart snippet

from openpyxl.chart import BarChart, Reference
from openpyxl.chart.shapes import GraphicalProperties

ch = BarChart()
ch.type = "col"     # vertical bars; "bar" = horizontal
ch.style = 2        # minimal style; we override colors anyway
ch.title = "Skill Invocations"
ch.width, ch.height = 20, 10
ch.legend = None

ch.add_data(Reference(ws, min_col=3, min_row=11, max_row=20), titles_from_data=False)
ch.set_categories(Reference(ws, min_col=2, min_row=11, max_row=20))

# Fill the bars with `ink` (from your palette dict)
ch.series[0].graphicalProperties = GraphicalProperties(solidFill=palette["ink"])

ws.add_chart(ch, "F22")

🧊 Frozen panes + alternating rows + conditional formatting

ws.freeze_panes = 'A12'  # header at row 11 stays visible

# Alternating row bands (apply via conditional formatting MOD)
from openpyxl.formatting.rule import FormulaRule
from openpyxl.styles import PatternFill
band = PatternFill(start_color=palette["paper_tint"],
                   end_color=palette["paper_tint"], fill_type='solid')
ws.conditional_formatting.add(
    f'A12:Z{last_row}',
    FormulaRule(formula=['MOD(ROW(),2)=0'], fill=band),
)

# Data bar (monochrome only) for a KPI column
from openpyxl.formatting.rule import DataBarRule
ws.conditional_formatting.add(
    'D12:D' + str(last_row),
    DataBarRule(start_type='min', end_type='max', color=palette["ink"]),
)

📝 Output checklist

• One palette, only its 4 hex values appear anywhere
• Only Cambria + Calibri (verify no Arial/Times slipped in)
• No 3-D, no shadows, no gradients, no rainbow conditional formatting
• Title row merged, frozen header at correct row
• All numbers have explicit Excel format codes
• Charts: ≤ 2 series, ink + accent only
• Alternating row bands applied
• No fabricated data; if KPIs require deltas, deltas come from real prior-period numbers

Then write the .xlsx and report path + which palette + which sections.