top-value-coloring

top-value-coloring is a skill for Claude Code, Codex from OpenSenseNova/SenseNova-Skills. It costs 45 tokens per session (1,089 once invoked), scanned A, original, MIT.

A workflow for combining data from multiple Excel sheets, finding the top results, and highlighting important values in a formatted workbook. It uses Python tools for reading, cleaning, analysing, and styling spreadsheet data.

In plain words
What is it for?
Use it to create Excel analysis reports with cleaned data, Top-N results, highlighted values, borders, and aligned cells.
Why use it?
It reduces the manual work of merging sheets, fixing missing or incorrectly typed values, selecting the highest results, and formatting reports.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create Excel analysis reports with cleaned data, Top-N results, highlighted values, borders, and aligned cells.

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Install with agentmods
npx agentmods add skills/opensensenova/sensenova-skills/top-value-coloring
About the project

SenseNova-Skills is a collection of modular skills that extend SenseNova models with office-assistant capabilities such as image generation, presentation creation, spreadsheet analysis, and research. The skills are designed for use in agent runtimes and can be combined into productivity workflows; the catalogue entries are individual skills and agents from this collection.

OpenSenseNova/SenseNova-Skills · 5,570 stars · on GitHub

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 OpenSenseNova/SenseNova-Skills --skill top-value-coloring
Clone the repo
git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills

Made for: Claude Code, Codex.

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 top-value-coloring

README.md
[![agentmods](https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/top-value-coloring/github.svg)](https://agentmods.dev/skills/opensensenova/sensenova-skills/top-value-coloring)
Your own site
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/top-value-coloring"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/top-value-coloring/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 top-value-coloring

Your own site · 80×15
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/top-value-coloring"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/top-value-coloring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,089 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00045 $0.01089
Opus 5 $0.00023 $0.00544
Sonnet 5 $0.00009 $0.00218
Haiku 4.5 $0.00005 $0.00109

Measured 12d ago against content hash 8dce83c3b9e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

top-value-coloring 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/sn-da-excel-workflow/capability/excel-cell-coloring/top-value-coloring/SKILL.md · 100 lines

What it actually says

Step1 提取并合并多个 Sheet 中的关键维度数据,进行数据清洗、类型转换及 Top-N 筛选。

# 示例:合并两个 Sheet 的数据
# 读取 Sheet1 并清洗
df1 = pd.read_excel(file_path, sheet_name='Sheet1', header=None)
# 假设 group_col 在第0列,value_col 在第2列
data1 = df1.iloc[20:, [0, 2]].copy()
data1.columns = ['group_col', 'value_col_1']
data1['value_col_1'] = pd.to_numeric(data1['value_col_1'], errors='coerce')
data1['group_col'] = data1['group_col'].ffill() # 处理合并单元格产生的缺失

# 读取 Sheet2 并清洗
df2 = pd.read_excel(file_path, sheet_name='Sheet2', header=None)
data2 = df2.iloc[5:, [0, 1]].copy()
data2.columns = ['value_col_2', 'value_col_3']

# 合并数据
merged_df = pd.concat([data1.reset_index(drop=True), data2.reset_index(drop=True)], axis=1)
merged_df = merged_df.dropna(subset=['value_col_1'])

# 筛选关键指标前五的数据
top_results = merged_df.nlargest(5, 'value_col_1').copy()

# 占位示例:修正特定缺失值
# top_results.loc[top_results['group_col'].isna(), 'group_col'] = 'Default_Value'

Step2 使用 openpyxl 创建格式化表格,应用条件样式(如特定列标红、最大值高亮)并设置边框与对齐方式。

from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side

output_path = 'analysis_report.xlsx'

# 创建工作簿
wb = Workbook()
ws = wb.active
ws.title = 'Analysis_Results'

# 定义样式
header_fill = PatternFill(start_color='4472C4', end_color='4472C4', fill_type='solid')
header_font = Font(bold=True, color='FFFFFF', size=12)
red_font = Font(color='FF0000', bold=True) # 用于高亮异常或关键值
green_fill = PatternFill(start_color='C6EFCE', end_color='C6EFCE', fill_type='solid') # 用于高亮最大值
thin_border = Border(left=Side(style='thin'), right=Side(style='thin'), 
                     top=Side(style='thin'), bottom=Side(style='thin'))
center_align = Alignment(horizontal='center', vertical='center')

# 写入表头
headers = ['Rank'] + list(top_results.columns)
for col, header in enumerate(headers, 1):
    cell = ws.cell(row=1, column=col, value=header)
    cell.font = header_font
    cell.fill = header_fill
    cell.alignment = center_align
    cell.border = thin_border

# 写入数据并应用样式
for idx, (_, row) in enumerate(top_results.iterrows(), 2):
    # 写入排名
    ws.cell(row=idx, column=1, value=idx-1).border = thin_border
    
    # 写入各列数据
    for col_idx, value in enumerate(row, 2):
        cell = ws.cell(row=idx, column=col_idx, value=value)
        cell.border = thin_border
        
        # 逻辑高亮示例:对特定列(如第4列)应用红色字体
        if col_idx == 4:
            cell.font = red_font
        
        # 逻辑高亮示例:对超过阈值的值应用绿色填充
        # if isinstance(value, (int, float)) and value > threshold_val:
        #     cell.fill = green_fill

# 自动调整列宽
column_widths = {'A': 8, 'B': 30, 'C': 15, 'D': 15, 'E': 18}
for col, width in column_widths.items():
    ws.column_dimensions[col].width = width

# 设置数字格式
for row in range(2, ws.max_row + 1):
    ws.cell(row=row, column=3).number_format = '#,##0'
    ws.cell(row=row, column=4).number_format = '#,##0.00'

wb.save(output_path)
print(f"Formatted file saved to: {output_path}")

Step3 生成并输出结果文件的下载链接。

# 必须使用 sandbox:/ 前缀生成下载链接
print(f"[下载分析结果]({f'sandbox:{output_path}'})")
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 · 100 lines · 45 tokens per session scan A 8dce83c3b9e8

Subscribe to this mod's changes

top-value-coloring is a skill published in the GitHub repository OpenSenseNova/SenseNova-Skills (5,570 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 1,089 once invoked, about $0.0002 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 2026-08-30.

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