xlsx

Name: xlsx
Author: stvlynn

118stars21forks

How to install xlsx?

stvlynn/dingtalk-wukong-skills/xlsx

$npx -y skills add stvlynn/dingtalk-wukong-skills --skill xlsx

Installs into the current project.

Summary

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Read

Files · 1

View on GitHub

SKILL.md

1	# Excel电子表格处理专家 Real Skill
2
3	## 一句话说明
4
5	专业的 Excel 处理工具，强制零公式错误标准，支持数据分析、报表生成和财务建模。
6
7	Excel Spreadsheet Mastery - Zero-error formula standard, data analysis, automated reporting, financial modeling with color coding.
8
9	---
10
11	## 使用场景
12
13	适用：
14	- 数据分析和统计报告
15	- 自动化生成 Excel 报表
16	- 财务预测模型（色彩编码）
17	- 批量处理多个 Excel 文件
18	- 数据清洗和格式转换
19
20	不适用：
21	- 实时协同编辑（用 Google Sheets / use Google Sheets for real-time collaboration）
22	- 复杂宏操作（用 VBA / use VBA for complex macros）
23
24	---
25
26	## 核心流程
27
28	```
29	用户需求 → 判断任务类型 → 选择工具 → 执行操作 → 公式重算 → 验证输出
30	User request → Task classification → Tool selection → Execute → Recalc formulas → Validate
31	```
32
33	任务类型判断 (Task Classification)：
34
35	### Data Analysis (数据分析)
36	- Simple analysis → pandas (read, analyze, visualize)
37	- Statistical reports → pandas + matplotlib/seaborn
38	- Data cleaning → pandas transformations
39
40	### Spreadsheet Creation (创建电子表格)
41	- With formulas → openpyxl + recalc.py (MANDATORY)
42	- Without formulas → pandas (faster)
43	- Financial models → openpyxl + color coding + recalc.py
44
45	### Editing Existing (编辑已有文件)
46	- Data updates → openpyxl (preserves formulas)
47	- Template modifications → Match existing format EXACTLY
48
49	⚠️ CRITICAL: After using formulas, MUST run `python scripts/recalc.py output.xlsx`
50
51	---
52
53	## 任务完成标准
54
55	必须满足（缺一不可）：
56	- ✅ 零公式错误 (Zero Formula Errors)（#REF!, #DIV/0!, #VALUE!, #N/A, #NAME? = 0）
57	- Excel 文件可正常打开
58	- 数据完整准确
59	- 格式规范（数字格式、对齐、边框）
60	- 财务模型使用行业标准色彩编码（如适用）
61
62	质量评级：
63	- ⭐⭐⭐⭐⭐ 优秀 - 零错误 + 色彩编码 + 完整文档
64	- ⭐⭐⭐ 及格 - 零错误 + 数据正确
65	- ⭐ 失败 - 存在公式错误
66
67	---
68
69	## 参考资料（供 AI 使用）
70
71	\| 类型 \| 路径 \| 说明 \|
72	\|-----\|------\|------\|
73	\| 核心文档 \| `docs/00-SKILL-完整操作指南.md` \| Complete Excel processing guide (~300 lines) \|
74	\| 工具脚本 \| `scripts/recalc.py` \| Formula recalculation script (requires LibreOffice) \|
75
76	---
77
78	## 关键原则（AI 必读 / Critical Principles）
79
80	### 1. ⚠️ Zero Formula Errors (零公式错误原则 - MANDATORY)
81	Every Excel file MUST be delivered with ZERO formula errors:
82	- No #REF! (invalid references)
83	- No #DIV/0! (division by zero)
84	- No #VALUE! (wrong data type)
85	- No #N/A (lookup not found)
86	- No #NAME? (unrecognized formula name)
87
88	Verification workflow:
89	```bash
90	python scripts/recalc.py output.xlsx
91	# Check JSON output: status should be "success"
92	# If "errors_found", fix and recalculate
93	```
94
95	### 2. Use Formulas, Not Hardcoded Values (使用公式而非硬编码)
96	CRITICAL: Always use Excel formulas instead of calculating in Python.
97
98	❌ WRONG - Hardcoding:
99	```python
100	total = df['Sales'].sum()
101	sheet['B10'] = total # Hardcodes 5000
102	```
103
104	✅ CORRECT - Using Formulas:
105	```python
106	sheet['B10'] = '=SUM(B2:B9)' # Dynamic formula
107	```
108
109	Why: Spreadsheet remains dynamic and updateable when source data changes.
110
111	### 3. Financial Modeling Color Coding (财务建模色彩编码)
112	Industry-standard color conventions (unless user specifies otherwise):
113
114	```python
115	from openpyxl.styles import Font
116
117	# Blue text (0000FF): User inputs and assumptions
118	ws['A1'].font = Font(color='0000FF')
119
120	# Black text (000000): ALL formulas and calculations
121	ws['B1'].font = Font(color='000000')
122
123	# Green text (008000): Links within same workbook
124	ws['C1'].font = Font(color='008000')
125
126	# Red text (FF0000): External file links
127	ws['D1'].font = Font(color='FF0000')
128
129	# Yellow background (FFFF00): Key assumptions
130	from openpyxl.styles import PatternFill
131	ws['E1'].fill = PatternFill(start_color='FFFF00', fill_type='solid')
132	```
133
134	### 4. Number Formatting Standards (数字格式标准)
135	```python
136	from openpyxl.styles import numbers
137
138	# Years: Format as text strings "2024" (not numbers)
139	ws['A1'].number_format = '@' # Text format
140	ws['A1'] = "'2024" # Force text
141
142	# Currency: $#,##0 + specify units in header
143	ws['B1'].number_format = '$#,##0'
144
145	# Zeros: Format as "-"
146	ws['C1'].number_format = '$#,##0;($#,##0);"-"'
147
148	# Percentages: 0.0% (one decimal)
149	ws['D1'].number_format = '0.0%'
150
151	# Multiples: 0.0x for valuation multiples
152	ws['E1'].number_format = '0.0"x"'
153
154	# Negative numbers: Use parentheses (123) not minus -123
155	ws['F1'].number_format = '#,##0;(#,##0)'
156	```
157
158	### 5. Preserve Existing Templates (保留现有模板)
159	When modifying existing files:
160	- Study and EXACTLY match existing format, style, conventions
161	- Never impose standardized formatting on files with established patterns
162	- Existing template conventions ALWAYS override these guidelines
163
164	---
165
166	## 快速命令参考 (Quick Commands)
167
168	### Data Analysis with Pandas (数据分析)
169	```python
170	import pandas as pd
171
172	# Read Excel (single sheet or all)
173	df = pd.read_excel('file.xlsx') # First sheet
174	all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict

People who liked this also viewed

6 picks

Type

xlsx

118stars21forks

View on GitHub

How to install xlsx?

stvlynn/dingtalk-wukong-skills/xlsx

$npx -y skills add stvlynn/dingtalk-wukong-skills --skill xlsx

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Excel电子表格处理专家 Real Skill
2
3	## 一句话说明
4
5	专业的 Excel 处理工具，强制零公式错误标准，支持数据分析、报表生成和财务建模。
6
7	Excel Spreadsheet Mastery - Zero-error formula standard, data analysis, automated reporting, financial modeling with color coding.
8
9	---
10
11	## 使用场景
12
13	适用：
14	- 数据分析和统计报告
15	- 自动化生成 Excel 报表
16	- 财务预测模型（色彩编码）
17	- 批量处理多个 Excel 文件
18	- 数据清洗和格式转换
19
20	不适用：
21	- 实时协同编辑（用 Google Sheets / use Google Sheets for real-time collaboration）
22	- 复杂宏操作（用 VBA / use VBA for complex macros）
23
24	---
25
26	## 核心流程
27
28	```
29	用户需求 → 判断任务类型 → 选择工具 → 执行操作 → 公式重算 → 验证输出
30	User request → Task classification → Tool selection → Execute → Recalc formulas → Validate
31	```
32
33	任务类型判断 (Task Classification)：
34
35	### Data Analysis (数据分析)
36	- Simple analysis → pandas (read, analyze, visualize)
37	- Statistical reports → pandas + matplotlib/seaborn
38	- Data cleaning → pandas transformations
39
40	### Spreadsheet Creation (创建电子表格)
41	- With formulas → openpyxl + recalc.py (MANDATORY)
42	- Without formulas → pandas (faster)
43	- Financial models → openpyxl + color coding + recalc.py
44
45	### Editing Existing (编辑已有文件)
46	- Data updates → openpyxl (preserves formulas)
47	- Template modifications → Match existing format EXACTLY
48
49	⚠️ CRITICAL: After using formulas, MUST run `python scripts/recalc.py output.xlsx`
50
51	---
52
53	## 任务完成标准
54
55	必须满足（缺一不可）：
56	- ✅ 零公式错误 (Zero Formula Errors)（#REF!, #DIV/0!, #VALUE!, #N/A, #NAME? = 0）
57	- Excel 文件可正常打开
58	- 数据完整准确
59	- 格式规范（数字格式、对齐、边框）
60	- 财务模型使用行业标准色彩编码（如适用）
61
62	质量评级：
63	- ⭐⭐⭐⭐⭐ 优秀 - 零错误 + 色彩编码 + 完整文档
64	- ⭐⭐⭐ 及格 - 零错误 + 数据正确
65	- ⭐ 失败 - 存在公式错误
66
67	---
68
69	## 参考资料（供 AI 使用）
70
71	\| 类型 \| 路径 \| 说明 \|
72	\|-----\|------\|------\|
73	\| 核心文档 \| `docs/00-SKILL-完整操作指南.md` \| Complete Excel processing guide (~300 lines) \|
74	\| 工具脚本 \| `scripts/recalc.py` \| Formula recalculation script (requires LibreOffice) \|
75
76	---
77
78	## 关键原则（AI 必读 / Critical Principles）
79
80	### 1. ⚠️ Zero Formula Errors (零公式错误原则 - MANDATORY)
81	Every Excel file MUST be delivered with ZERO formula errors:
82	- No #REF! (invalid references)
83	- No #DIV/0! (division by zero)
84	- No #VALUE! (wrong data type)
85	- No #N/A (lookup not found)
86	- No #NAME? (unrecognized formula name)
87
88	Verification workflow:
89	```bash
90	python scripts/recalc.py output.xlsx
91	# Check JSON output: status should be "success"
92	# If "errors_found", fix and recalculate
93	```
94
95	### 2. Use Formulas, Not Hardcoded Values (使用公式而非硬编码)
96	CRITICAL: Always use Excel formulas instead of calculating in Python.
97
98	❌ WRONG - Hardcoding:
99	```python
100	total = df['Sales'].sum()
101	sheet['B10'] = total # Hardcodes 5000
102	```
103
104	✅ CORRECT - Using Formulas:
105	```python
106	sheet['B10'] = '=SUM(B2:B9)' # Dynamic formula
107	```
108
109	Why: Spreadsheet remains dynamic and updateable when source data changes.
110
111	### 3. Financial Modeling Color Coding (财务建模色彩编码)
112	Industry-standard color conventions (unless user specifies otherwise):
113
114	```python
115	from openpyxl.styles import Font
116
117	# Blue text (0000FF): User inputs and assumptions
118	ws['A1'].font = Font(color='0000FF')
119
120	# Black text (000000): ALL formulas and calculations
121	ws['B1'].font = Font(color='000000')
122
123	# Green text (008000): Links within same workbook
124	ws['C1'].font = Font(color='008000')
125
126	# Red text (FF0000): External file links
127	ws['D1'].font = Font(color='FF0000')
128
129	# Yellow background (FFFF00): Key assumptions
130	from openpyxl.styles import PatternFill
131	ws['E1'].fill = PatternFill(start_color='FFFF00', fill_type='solid')
132	```
133
134	### 4. Number Formatting Standards (数字格式标准)
135	```python
136	from openpyxl.styles import numbers
137
138	# Years: Format as text strings "2024" (not numbers)
139	ws['A1'].number_format = '@' # Text format
140	ws['A1'] = "'2024" # Force text
141
142	# Currency: $#,##0 + specify units in header
143	ws['B1'].number_format = '$#,##0'
144
145	# Zeros: Format as "-"
146	ws['C1'].number_format = '$#,##0;($#,##0);"-"'
147
148	# Percentages: 0.0% (one decimal)
149	ws['D1'].number_format = '0.0%'
150
151	# Multiples: 0.0x for valuation multiples
152	ws['E1'].number_format = '0.0"x"'
153
154	# Negative numbers: Use parentheses (123) not minus -123
155	ws['F1'].number_format = '#,##0;(#,##0)'
156	```
157
158	### 5. Preserve Existing Templates (保留现有模板)
159	When modifying existing files:
160	- Study and EXACTLY match existing format, style, conventions
161	- Never impose standardized formatting on files with established patterns
162	- Existing template conventions ALWAYS override these guidelines
163
164	---
165
166	## 快速命令参考 (Quick Commands)
167
168	### Data Analysis with Pandas (数据分析)
169	```python
170	import pandas as pd
171
172	# Read Excel (single sheet or all)
173	df = pd.read_excel('file.xlsx') # First sheet
174	all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # All sheets as dict

People who liked this also viewed

6 picks

Type