xlsx

Name: xlsx
Author: kv0906

134stars33forks

How to install xlsx?

kv0906/pm-kit/xlsx

$npx -y skills add kv0906/pm-kit --skill xlsx

Installs into the current project.

Summary

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); cre

Files · 1

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SKILL.md

1	# Requirements for Outputs
2
3	## All Excel files
4
5	### Professional Font
6	- Use a consistent, professional font (e.g., Arial, Times New Roman) for all deliverables unless otherwise instructed by the user
7
8	### Zero Formula Errors
9	- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
10
11	### Preserve Existing Templates (when updating templates)
12	- Study and EXACTLY match existing format, style, and conventions when modifying files
13	- Never impose standardized formatting on files with established patterns
14	- Existing template conventions ALWAYS override these guidelines
15
16	## Financial models
17
18	### Color Coding Standards
19	Unless otherwise stated by the user or existing template
20
21	#### Industry-Standard Color Conventions
22	- Blue text (RGB: 0,0,255): Hardcoded inputs, and numbers users will change for scenarios
23	- Black text (RGB: 0,0,0): ALL formulas and calculations
24	- Green text (RGB: 0,128,0): Links pulling from other worksheets within same workbook
25	- Red text (RGB: 255,0,0): External links to other files
26	- Yellow background (RGB: 255,255,0): Key assumptions needing attention or cells that need to be updated
27
28	### Number Formatting Standards
29
30	#### Required Format Rules
31	- Years: Format as text strings (e.g., "2024" not "2,024")
32	- Currency: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
33	- Zeros: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
34	- Percentages: Default to 0.0% format (one decimal)
35	- Multiples: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)
36	- Negative numbers: Use parentheses (123) not minus -123
37
38	### Formula Construction Rules
39
40	#### Assumptions Placement
41	- Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells
42	- Use cell references instead of hardcoded values in formulas
43	- Example: Use =B5(1+$B$6) instead of =B51.05
44
45	#### Formula Error Prevention
46	- Verify all cell references are correct
47	- Check for off-by-one errors in ranges
48	- Ensure consistent formulas across all projection periods
49	- Test with edge cases (zero values, negative numbers)
50	- Verify no unintended circular references
51
52	#### Documentation Requirements for Hardcodes
53	- Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"
54	- Examples:
55	- "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]"
56	- "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]"
57	- "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity"
58	- "Source: FactSet, 8/20/2025, Consensus Estimates Screen"
59
60	# XLSX creation, editing, and analysis
61
62	## Overview
63
64	A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have different tools and workflows available for different tasks.
65
66	## Important Requirements
67
68	LibreOffice Required for Formula Recalculation: You can assume LibreOffice is installed for recalculating formula values using the `scripts/recalc.py` script. The script automatically configures LibreOffice on first run, including in sandboxed environments where Unix sockets are restricted (handled by `scripts/office/soffice.py`)
69
70	## Reading and analyzing data
71
72	### Data analysis with pandas
73	For data analysis, visualization, and basic operations, use pandas which provides powerful data manipulation capabilities:
74
75	```python
76	import pandas as pd
77
78	# Read Excel
79	df = pd.read_excel('file.xlsx') # Default: first sheet
80	all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict
81
82	# Analyze
83	df.head() # Preview data
84	df.info() # Column info
85	df.describe() # Statistics
86
87	# Write Excel
88	df.to_excel('output.xlsx', index=False)
89	```
90
91	## Excel File Workflows
92
93	## CRITICAL: Use Formulas, Not Hardcoded Values
94
95	Always use Excel formulas instead of calculating values in Python and hardcoding them. This ensures the spreadsheet remains

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Type

xlsx

134stars33forks

View on GitHub

How to install xlsx?

kv0906/pm-kit/xlsx

$npx -y skills add kv0906/pm-kit --skill xlsx

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Requirements for Outputs
2
3	## All Excel files
4
5	### Professional Font
6	- Use a consistent, professional font (e.g., Arial, Times New Roman) for all deliverables unless otherwise instructed by the user
7
8	### Zero Formula Errors
9	- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
10
11	### Preserve Existing Templates (when updating templates)
12	- Study and EXACTLY match existing format, style, and conventions when modifying files
13	- Never impose standardized formatting on files with established patterns
14	- Existing template conventions ALWAYS override these guidelines
15
16	## Financial models
17
18	### Color Coding Standards
19	Unless otherwise stated by the user or existing template
20
21	#### Industry-Standard Color Conventions
22	- Blue text (RGB: 0,0,255): Hardcoded inputs, and numbers users will change for scenarios
23	- Black text (RGB: 0,0,0): ALL formulas and calculations
24	- Green text (RGB: 0,128,0): Links pulling from other worksheets within same workbook
25	- Red text (RGB: 255,0,0): External links to other files
26	- Yellow background (RGB: 255,255,0): Key assumptions needing attention or cells that need to be updated
27
28	### Number Formatting Standards
29
30	#### Required Format Rules
31	- Years: Format as text strings (e.g., "2024" not "2,024")
32	- Currency: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
33	- Zeros: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
34	- Percentages: Default to 0.0% format (one decimal)
35	- Multiples: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)
36	- Negative numbers: Use parentheses (123) not minus -123
37
38	### Formula Construction Rules
39
40	#### Assumptions Placement
41	- Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells
42	- Use cell references instead of hardcoded values in formulas
43	- Example: Use =B5(1+$B$6) instead of =B51.05
44
45	#### Formula Error Prevention
46	- Verify all cell references are correct
47	- Check for off-by-one errors in ranges
48	- Ensure consistent formulas across all projection periods
49	- Test with edge cases (zero values, negative numbers)
50	- Verify no unintended circular references
51
52	#### Documentation Requirements for Hardcodes
53	- Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"
54	- Examples:
55	- "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]"
56	- "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]"
57	- "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity"
58	- "Source: FactSet, 8/20/2025, Consensus Estimates Screen"
59
60	# XLSX creation, editing, and analysis
61
62	## Overview
63
64	A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have different tools and workflows available for different tasks.
65
66	## Important Requirements
67
68	LibreOffice Required for Formula Recalculation: You can assume LibreOffice is installed for recalculating formula values using the `scripts/recalc.py` script. The script automatically configures LibreOffice on first run, including in sandboxed environments where Unix sockets are restricted (handled by `scripts/office/soffice.py`)
69
70	## Reading and analyzing data
71
72	### Data analysis with pandas
73	For data analysis, visualization, and basic operations, use pandas which provides powerful data manipulation capabilities:
74
75	```python
76	import pandas as pd
77
78	# Read Excel
79	df = pd.read_excel('file.xlsx') # Default: first sheet
80	all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict
81
82	# Analyze
83	df.head() # Preview data
84	df.info() # Column info
85	df.describe() # Statistics
86
87	# Write Excel
88	df.to_excel('output.xlsx', index=False)
89	```
90
91	## Excel File Workflows
92
93	## CRITICAL: Use Formulas, Not Hardcoded Values
94
95	Always use Excel formulas instead of calculating values in Python and hardcoding them. This ensures the spreadsheet remains

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6 picks

Type