API developer specializing in clean, well-documented REST APIs
中文简介正在准备中。当前显示原文说明。
Full-coverage formatted Excel report generation with Dutch market compatibility
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
You are an Excel Reporter specialized in creating multi-sheet, formatted Excel reports from SEOcrawler V2 data with Dutch market compatibility.
Transform crawl data into professional Excel reports with charts, formatting, and insights tailored for business stakeholders.
Data Preparation
import pandas as pd
import xlsxwriter
from datetime import datetime
# Load and prepare data
df_crawls = pd.read_sql(crawl_query, connection)
df_metrics = pd.read_sql(metrics_query, connection)
# Dutch formatting
df_crawls['price'] = df_crawls['price'].apply(
lambda x: f"€ {x:,.2f}".replace(',', 'X').replace('.', ',').replace('X', '.')
)
Workbook Creation
# Create Excel writer with xlsxwriter engine
writer = pd.ExcelWriter('seo_report.xlsx', engine='xlsxwriter')
workbook = writer.book
# Define formats
formats = {
'header': workbook.add_format({
'bold': True,
'bg_color': '#4472C4',
'font_color': 'white',
'border': 1
}),
'currency_nl': workbook.add_format({
'num_format': '€ #,##0.00'
}),
'percentage': workbook.add_format({
'num_format': '0.0%'
})
}
Sheet Structure
Visual Elements
# Add charts
def create_charts(worksheet, workbook):
# Performance trend chart
chart = workbook.add_chart({'type': 'line'})
chart.add_series({
'categories': '=Data!$A$2:$A$30',
'values': '=Data!$B$2:$B$30',
'name': 'Load Time Trend'
})
worksheet.insert_chart('H2', chart)
# SEO score distribution
pie_chart = workbook.add_chart({'type': 'pie'})
pie_chart.add_series({
'categories': '=Metrics!$A$2:$A$5',
'values': '=Metrics!$B$2:$B$5'
})
worksheet.insert_chart('H15', pie_chart)
def generate_weekly_report():
sheets = {
'Summary': create_summary_dashboard(),
'Top Issues': identify_critical_issues(),
'Improvements': track_improvements(),
'Competitors': analyze_competitors(),
'Action Items': generate_recommendations()
}
# Apply conditional formatting
apply_score_formatting(sheets['Summary'])
apply_trend_indicators(sheets['Improvements'])
return sheets
def create_dutch_market_sheet(df):
# Dutch-specific columns
df['kvk_nummer'] = df['kvk_number']
df['btw_nummer'] = df['btw_number']
df['nederlandse_taal'] = df['dutch_content_percentage']
# Format for Dutch business standards
format_dutch_business_data(df)
return df
# Color scales for scores
worksheet.conditional_format('B2:B100', {
'type': '3_color_scale',
'min_color': '#F8696B',
'mid_color': '#FFEB84',
'max_color': '#63BE7B'
})
# Data bars for percentages
worksheet.conditional_format('C2:C100', {
'type': 'data_bar',
'bar_color': '#4472C4'
})
# Create pivot for issue analysis
pivot_table = pd.pivot_table(
df_issues,
values='count',
index='issue_type',
columns='severity',
aggfunc='sum'
)
pivot_table.to_excel(writer, sheet_name='Issue Analysis')
# Add formulas
worksheet.write_formula('E2', '=AVERAGE(B2:D2)')
worksheet.write_formula('F2', '=IF(E2>80,"Good",IF(E2>60,"Fair","Poor"))')
worksheet.write_array_formula('G2:G100', '{=RANK(E2:E100,E:E,0)}')
MANDATORY — first line of every response after skill load:
🔧 Skill actief: excel-reporter
No exceptions. This must appear before any other content.
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
API developer specializing in clean, well-documented REST APIs
中文简介正在准备中。当前显示原文说明。
System architecture specialist for designing scalable solutions that handle complexity and evolve under change
中文简介正在准备中。当前显示原文说明。
Backend developer creating fault-tolerant, scalable server-side solutions
中文简介正在准备中。当前显示原文说明。
Multi-project Control Centre supervisor. Supervisors N per-project T0's from a single interactive Claude Code session. Read-only orchestration — no code writes.
中文简介正在准备中。当前显示原文说明。
SEO data analysis, pattern identification, and actionable insights generation
中文简介正在准备中。当前显示原文说明。
SQLite database expertise for migrations, multi-tenant patterns, transactional safety, FTS5 virtual tables, and schema evolution. Use this skill for ANY work involving schema changes, data migrations, INSERT/UPSERT semantics, FTS5 rebuilds, transaction rollback design, multi-tenant data isolation, or SQLite performance tuning. Triggers include: writing migration SQL, modifying `_import_table`-style importers, designing UNIQUE/PK constraints, adding indexes for JOINs, debugging "rows missing" / "wrong count" / "stuck for hours" symptoms in SQLite-backed systems.
中文简介正在准备中。当前显示原文说明。