A complete Python-powered Excel workflow for creating, cleaning, formatting, analyzing, converting, and exporting spreadsheet data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install excel-skills
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install excel-skills using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Excel Processing Toolkit?
Excel Processing Toolkit is one of the practical Openclaw Skills for end-to-end spreadsheet automation. It supports workbook creation, reading, editing, formatting, multi-sheet management, CSV and JSON data pipelines, PDF table conversion, crawler data exports, and structured report generation.
Built around openpyxl and pandas, the skill also includes reusable logic in scripts/excel_toolkit.py for standardized reports with styled headers, frozen panes, and adaptive column widths. It provides safeguards for common openpyxl style-type errors, formula reading behavior, Windows encoding issues, and large-file performance limits.
Excel Processing Toolkit Use Cases
- Create new
.xlsxworkbooks and populate them with structured records. - Read existing Excel files while retrieving cached formula results with
data_only=True. - Edit cell values, apply professional formatting, set number formats, resize columns, and freeze headers.
- Clean and transform tabular data with pandas before exporting it to Excel or CSV.
- Combine summaries and details across multiple worksheets.
- Convert extracted PDF tables into Excel workbooks.
- Export crawler, product, or batch-processing results into reusable spreadsheet files.
- Generate polished analysis reports with consistent headers, layout, and formatting.
- Read from and write to Feishu cloud spreadsheets for collaborative workflows.
- Use Openclaw Skills to automate recurring spreadsheet operations while preserving validation and backup practices.
How Excel Processing Toolkit Works
- Identify the requested operation: create, read, edit, export, analyze, or convert a spreadsheet.
- Verify that source files exist and confirm the relevant format and encoding.
- Reuse the appropriate functions from
scripts/excel_toolkit.pyinstead of duplicating established workbook logic. - Select the processing layer: openpyxl for workbook-level reading and editing, or pandas for tabular cleaning, transformation, and bulk export.
- Load workbooks with
data_only=Truewhen cached formula results are required, recognizing that the workbook must previously have been saved by Excel or another calculation engine. - Apply styles independently by type, constructing separate
Font,Fill,Border, andAlignmentobjects to avoid openpyxl type conflicts. - Manage worksheets by creating, ordering, iterating, merging, or removing sheets as needed.
- Export the result to
.xlsx,.csv, or another supported destination, usingutf-8-sigfor CSV files intended to open correctly in Excel. - Validate the output by checking row counts, headers, representative cell values, sheet names, and formatting.
- Back up original files before performing large or destructive operations.
Excel Processing Toolkit Setup
Requirements
Use Python 3.8 or later. The core dependencies are openpyxl and pandas; xlsxwriter and PDF extraction libraries are optional depending on the workflow.
python -m pip install openpyxl pandas
For PDF table extraction with the documented pdfplumber example, install the additional dependency:
python -m pip install pdfplumber
Installation and configuration
- Place the skill in the agent's skills directory and preserve the reusable
scripts/excel_toolkit.pyfile. - Confirm input and output paths before execution.
- Use openpyxl when an existing workbook must be read or modified.
- Use pandas for data cleaning, format conversion, and bulk tabular exports.
- Optionally use
xlsxwriterfor fast, one-time generation of large reports; it does not read or modify existing workbooks. - For Feishu cloud spreadsheet workflows, configure the required Feishu integration and spreadsheet token before calling
read_range,write_range, orappend. - On Windows, configure Python output as UTF-8 when printing Chinese text to PowerShell:
python -c "import sys; sys.stdout.reconfigure(encoding='utf-8')"
- Test with a small workbook before processing large files or overwriting source data.
Excel Processing Toolkit Data Schema & Taxonomy
Supported data layers
| Layer | Formats or objects | Primary purpose |
|---|---|---|
| Workbook | .xlsx and worksheets |
Cell-level creation, reading, editing, styling, and sheet management |
| Tabular data | pandas DataFrame |
Cleaning, deduplication, missing-value handling, date parsing, and bulk export |
| Interchange files | .csv and .json |
Import and export between common structured-data formats |
| Document extraction | PDF tables | Convert extracted table arrays into Excel worksheets |
| Cloud spreadsheet | Feishu spreadsheet token and range | Collaborative read, write, and append operations |
Workbook organization
scripts/excel_toolkit.py: reusable one-stop toolkit for reading xlsx, CSV, and JSON data; generating formatted reports; converting PDF tables; and merging multiple sheets.- Worksheets are identified by name and may contain source data, summaries, details, analysis output, or temporary processing data.
- Report metadata includes styled header rows, frozen header panes, adaptive column widths, row heights, and number formats.
- Common number formats include
#,##0.00for amounts,0.00%for percentages, andyyyy-mm-ddfor dates. - Cleaned datasets may include filled numeric or categorical nulls, removed duplicates, and normalized date columns.
- CSV exports should use
utf-8-sigwhen compatibility with direct Excel opening is required. - Feishu operations use a
spreadsheet_tokenplus A1-style ranges such asSheet1!A1:C10.
Validation metadata
After execution, verify file existence, worksheet names, dimensions, header values, sample cells, and expected output encoding. For high-volume operations, retain a backup of the original workbook.
Excel Processing Toolkit Advanced Features
- Reusable
scripts/excel_toolkit.pyfunctions reduce duplicated spreadsheet automation code. - Multi-sheet workflows support insertion at a specific position, iteration, inspection, deletion, and multi-DataFrame export.
- Styled report generation can standardize headers, freeze panes, and automatically size columns.
- Separate construction and assignment of openpyxl style objects prevents
Fill,Border,Alignment, andFonttype-mixing failures. - Formula-aware reading distinguishes formula expressions from cached calculation results.
- Performance guidance recommends
ws.append()or pandas pipelines for high-volume writes rather than assigning cells individually. xlsxwritercan be selected for fast, one-time generation of large reports, while openpyxl remains the read-and-modify option.- PDF table extraction and crawler-result exports extend the skill beyond ordinary workbook editing.
- Feishu cloud spreadsheet actions support range reads, range writes, and append operations for collaborative automation.
- Windows encoding safeguards help prevent garbled Chinese output in PowerShell and Excel-opened CSV files.
- Openclaw Skills integration enables repeatable spreadsheet tasks with explicit output checks, safe backups, and workflow-specific tool selection.
SKILL.md
Loading
Related Openclaw Skills
Xiangsheng Writer
A guided AI writing workflow that turns a topic into a polished, stage-ready Chinese xiangsheng script.
SN Deep Research
SN Deep Research orchestrates multi-agent research, evidence validation, citation rendering, and report production across quick, normal, and heavy workflows.
Mifu Chemistry Lesson Prep
An AI-powered chemistry lesson-preparation workflow that produces teacher lesson plans and student study guides tailored to topic, level, region, and learner needs.
Chem-Viz Chemistry Visualization
Chem-Viz turns abstract chemistry concepts into interactive, classroom-ready HTML visualizations that students can explore and understand.
Long Task Runner
Long Task Runner executes slow local commands and queued workloads with controlled waiting, safe recovery, bounded logs, and evidence-based completion checks.
Ståle Einarsen Workplace Bullying & NAQ Framework
A research-grounded framework for defining, measuring, distinguishing, and diagnosing workplace bullying using Einarsen’s model and the NAQ.
Featured*
