wps-data-viz

wps-data-viz is a skill for Claude Code from Bwkyd/wps-skills. It costs 94 tokens per session (1,926 once invoked), scanned A, original, MIT.

An Excel data-dashboard generator that turns source data into one-page KPI cards, trend lines, pie charts, ranking bars, and summary tables.

In plain words
What is it for?
Use it to create KPI dashboards and data overviews in Excel, including revenue, orders, average order value, conversion rate, trends, category shares, and rankings.
Why use it?
It puts key figures and common charts together so monthly or quarterly performance can be understood at a glance.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to create KPI dashboards and data overviews in Excel, including revenue, orders, average order value, conversion rate, trends, category shares, and rankings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bwkyd/wps-skills/wps-data-viz
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Bwkyd/wps-skills --skill wps-data-viz
Clone the repo
git clone --depth 1 https://github.com/Bwkyd/wps-skills

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for wps-data-viz

README.md
[![agentmods](https://agentmods.dev/badge/skills/bwkyd/wps-skills/wps-data-viz/github.svg)](https://agentmods.dev/skills/bwkyd/wps-skills/wps-data-viz)
Your own site
<a href="https://agentmods.dev/skills/bwkyd/wps-skills/wps-data-viz"><img src="https://agentmods.dev/badge/skills/bwkyd/wps-skills/wps-data-viz/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for wps-data-viz

Your own site · 80×15
<a href="https://agentmods.dev/skills/bwkyd/wps-skills/wps-data-viz"><img src="https://agentmods.dev/badge/skills/bwkyd/wps-skills/wps-data-viz.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,926 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00094 $0.01926
Opus 5 $0.00047 $0.00963
Sonnet 5 $0.00019 $0.00385
Haiku 4.5 $0.00009 $0.00193

Measured 12d ago against content hash e367f179fd0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

wps-data-viz scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/wps-data-viz/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

数据可视化仪表盘

数据 → KPI卡片 + 趋势图 + 占比图 → 一页式数据概览。

不用Power BI,Excel也能做出专业仪表盘。

When to Use

  • 制作数据概览/仪表盘
  • 月度/季度数据一页展示
  • KPI指标可视化
  • 用户说"做个数据仪表盘""数据大屏"

When NOT to Use

  • 单个图表 → 使用 wps-chart
  • 数据透视分析 → 使用 wps-pivot

仪表盘布局

┌─────────┬─────────┬─────────┬─────────┐
│  KPI 1  │  KPI 2  │  KPI 3  │  KPI 4  │
│ 总收入  │ 订单数  │ 客单价  │ 转化率  │
│ ¥125万  │ 3,456  │ ¥362   │ 4.2%   │
│ ↑12.5%  │ ↑8.3%  │ ↓2.1%  │ ↑0.5%  │
├─────────┴─────────┼─────────┴─────────┤
│                    │                    │
│  收入趋势折线图    │  品类占比饼图      │
│  (12个月)          │                    │
│                    │                    │
├────────────────────┼────────────────────┤
│                    │                    │
│  TOP10产品柱状图   │  地区分布表格      │
│                    │                    │
└────────────────────┴────────────────────┘

工作流程

Step 1: 确认仪表盘要素

  • KPI指标:需要展示哪些关键数字
  • 趋势图:哪些数据看趋势
  • 占比图:哪些数据看构成
  • 排名表:哪些数据看排名
  • 数据源:数据在哪里

Step 2: 生成仪表盘

from openpyxl import Workbook
from openpyxl.chart import BarChart, LineChart, PieChart, Reference
from openpyxl.chart.label import DataLabelList
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
from openpyxl.utils import get_column_letter
import os

def create_dashboard(kpis, charts_data, output_path=None):
    """
    kpis = [
        {'name': '总收入', 'value': '¥125万', 'change': '+12.5%', 'trend': 'up'},
        {'name': '订单数', 'value': '3,456', 'change': '+8.3%', 'trend': 'up'},
    ]
    charts_data = {
        'trend': {'labels': [...], 'values': [...]},
        'pie': {'labels': [...], 'values': [...]},
        'bar': {'labels': [...], 'values': [...]},
    }
    """
    wb = Workbook()
    ws = wb.active
    ws.title = "数据仪表盘"
    ws.sheet_properties.tabColor = '2C3E50'

    # 隐藏网格线
    ws.sheet_view.showGridLines = False

    # KPI卡片
    kpi_colors = ['3498DB', '2ECC71', 'E74C3C', 'F39C12']
    for i, kpi in enumerate(kpis[:4]):
        col_start = i * 4 + 1
        ws.merge_cells(start_row=2, start_column=col_start,
                       end_row=2, end_column=col_start + 3)
        ws.merge_cells(start_row=3, start_column=col_start,
                       end_row=3, end_column=col_start + 3)
        ws.merge_cells(start_row=4, start_column=col_start,
                       end_row=4, end_column=col_start + 3)

        color = kpi_colors[i % len(kpi_colors)]
        fill = PatternFill('solid', fgColor=color)

        # 指标名
        cell = ws.cell(row=2, column=col_start, value=kpi['name'])
        cell.font = Font(name='微软雅黑', size=11, color='FFFFFF')
        cell.fill = fill
        cell.alignment = Alignment(horizontal='center')

        # 指标值
        cell = ws.cell(row=3, column=col_start, value=kpi['value'])
        cell.font = Font(name='微软雅黑', size=22, bold=True, color='FFFFFF')
        cell.fill = fill
        cell.alignment = Alignment(horizontal='center')

        # 变化
        arrow = '↑' if kpi.get('trend') == 'up' else '↓'
        cell = ws.cell(row=4, column=col_start,
                       value=f'{arrow} {kpi["change"]}')
        cell.font = Font(name='微软雅黑', size=10, color='FFFFFF')
        cell.fill = fill
        cell.alignment = Alignment(horizontal='center')

    # 数据区域(隐藏,供图表引用)
    data_start_row = 30
    if 'trend' in charts_data:
        td = charts_data['trend']
        for i, label in enumerate(td['labels']):
            ws.cell(row=data_start_row + i, column=1, value=label)
            ws.cell(row=data_start_row + i, column=2, value=td['values'][i])

        chart = LineChart()
        chart.title = "趋势"
        chart.width = 20
        chart.height = 12
        chart.style = 10
        data = Reference(ws, min_col=2, min_row=data_start_row,
                        max_row=data_start_row + len(td['labels']) - 1)
        cats = Reference(ws, min_col=1, min_row=data_start_row,
                        max_row=data_start_row + len(td['labels']) - 1)
        chart.add_data(data)
        chart.set_categories(cats)
        ws.add_chart(chart, 'A6')

    if 'pie' in charts_data:
        pd = charts_data['pie']
        for i, label in enumerate(pd['labels']):
            ws.cell(row=data_start_row + i, column=4, value=label)
            ws.cell(row=data_start_row + i, column=5, value=pd['values'][i])

        chart = PieChart()
        chart.title = "占比"
        chart.width = 14
        chart.height = 12
        data = Reference(ws, min_col=5, min_row=data_start_row,
                        max_row=data_start_row + len(pd['labels']) - 1)
        cats = Reference(ws, min_col=4, min_row=data_start_row,
                        max_row=data_start_row + len(pd['labels']) - 1)
        chart.add_data(data)
        chart.set_categories(cats)
        chart.dataLabels = DataLabelList()
        chart.dataLabels.showPercent = True
        ws.add_chart(chart, 'I6')

    if not output_path:
        output_path = '数据仪表盘.xlsx'
    wb.save(output_path)
    return os.path.abspath(output_path)

Read the full file on GitHub · 203 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 203 lines · 94 tokens per session scan A e367f179fd0c

Subscribe to this mod's changes

wps-data-viz is a skill published in the GitHub repository Bwkyd/wps-skills (8 stars, last pushed 4mo ago), licensed MIT. It adds 94 tokens to every session and 1,926 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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