feat: add new skills for context7-docs, cron-scheduling, excel-operations, hook-management, mcp-integration, notebook-edit, pdf-processing, and security-best-practices

2026-04-08 15:06:55 +07:00
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+---
+name: excel-operations
+description: Read, write, and manipulate Excel (.xlsx) and CSV files
+---
+
+## When to use
+Use when the user asks to:
+- Read data from Excel or CSV files
+- Create new spreadsheets
+- Update existing spreadsheet data
+- Perform calculations or data transformations
+- Export data to CSV/Excel format
+- Validate spreadsheet structure
+
+## Workflow
+
+### 1. Identify the file
+Determine file path and format (.xlsx, .csv, .tsv).
+
+### 2. Read the data
+
+OpenClaw's `read` is for text files. For Excel/CSV:
+
+**For CSV** (plain text):
+```bash
+read path/to/data.csv
+```
+
+**For .xlsx** (binary): Use Python or other tools:
+```bash
+python -c "
+import pandas as pd, json, sys;
+df = pd.read_excel('data.xlsx');
+print(df.to_json(orient='records'))
+"
+```
+
+Or install `xlsx2csv` and convert first:
+```bash
+xlsx2csv data.xlsx temp.csv
+read temp.csv
+```
+
+### 3. Process the data
+- Parse into structured format (list of objects, 2D array)
+- Validate headers/columns if needed
+- Perform transformations (filter, map, aggregate)
+
+### 4. Write results
+
+**For CSV**:
+```bash
+write output.csv --data "$csv_string"
+```
+
+**For .xlsx**: Use Python:
+```bash
+python -c "
+import pandas as pd, json, sys;
+data = json.loads(sys.argv[1]);
+pd.DataFrame(data).to_excel('output.xlsx', index=False)
+" "$structured_data"
+```
+
+## Supported Formats
+- **.xlsx** (Excel Open XML) — full support for sheets, formulas, formatting
+- **.csv** (Comma-separated) — plain text, delimiter detection
+- **.tsv** (Tab-separated) — tab delimiter
+
+## Common Operations
+
+### Read specific sheet
+```bash
+read file.xlsx --sheet "Sheet2"
+```
+
+### Read with range
+```bash
+read file.xlsx --range "A1:D100"
+```
+
+### Write with formatting
+```bash
+write report.xlsx \
+  --data "$table" \
+  --header true \
+  --autofit columns
+```
+
+### Append to existing file
+```bash
+write file.xlsx --data "$new_rows" --append true
+```
+
+## Data Structures
+
+**Reading returns**:
+```json
+{
+  "headers": ["Name", "Email", "Score"],
+  "rows": [
+    {"Name": "Alice", "Email": "a@example.com", "Score": 95},
+    ...
+  ]
+}
+```
+
+**Writing accepts**:
+- JSON array of objects
+- 2D array (array of arrays)
+- CSV string (if format=csv)
+
+## Examples
+
+<Good>
+User: "Tạo báo cáo điểm từ scores.csv"
+Assistant:
+1. Đọc scores.csv
+2. Tính toán điểm trung bình, xếp loại
+3. Ghi vào report.xlsx với định dạng đẹp
+4. Trả về đường dẫn file và tóm tắt kết quả
+</Good>
+
+<Bad>
+Ghi đè file gốc mà không backup, không thông báo.
+</Bad>
+
+## Error Handling
+- **File not found**: Kiểm tra đường dẫn, dùng `glob` để tìm
+- **Format mismatch**: Đảm bảo file đúng định dạng, kiểm tra extension
+- **Large files**: Có thể cần chunk processing, kiểm tra memory limits
+- **Corrupted data**: Catch parse errors, report specific row/column
+
+## Validation Checklist
+- [ ] File exists and is readable
+- [ ] Format matches extension
+- [ ] Headers are present and correct
+- [ ] Data types are correct (numbers, dates, strings)
+- [ ] No missing values in required columns
+- [ ] Output file is well-formed and complete