office-document-specialist-suite Practical Guide: Let AI Handle Your Word/Excel/PPT

Why We Started Using This Skill

Honestly, we found this skill because we were forced to. The boss sent a 48-page supplier contract in Word format, asking: "Clause 23's penalty amount doesn't match the numbers in Appendix B — can you check?" We tried feeding it directly to Claude, but Appendix B was embedded in an Excel spreadsheet. Claude couldn't read it. Manual copy-paste risked formatting errors. That's how we found office-document-specialist-suite.

What This Skill Does

It's an OpenClaw skill for handling Office document formats. Core capabilities:

Word (.docx): Full text including tables, headers/footers, comments, tracked changes
Excel (.xlsx/.xls): Multiple sheets, formula results (not formulas themselves), merged cells, pivot table summaries
PowerPoint (.pptx): Text from every slide, speaker notes, structured output
PDF (partial): Basic text extraction — complex layouts may lose formatting

Installation

clawhub install office-document-specialist-suite
openclaw gateway restart

Dependencies: python-docx, openpyxl, python-pptx. Install if missing:

pip3 install python-docx openpyxl python-pptx

⚠️ Gotcha: If you have multiple Python versions, make sure you're installing into the Python OpenClaw actually uses.

Use Case 1: Contract Review

Upload a Word file, then ask: "Find all clauses mentioning penalties and check if the amounts are consistent." Processing time for a 48-page contract: ~8–12 seconds. ⚠️ Comments and tracked changes aren't read by default — explicitly ask for them in your prompt.

Use Case 2: Excel Data Analysis

Upload Excel, ask: "What are Shanghai and Beijing's March sales figures? How do they compare to last month?" Works across sheets. Limitations: formulas return values only, charts can't be read, files over 100k rows get truncated.

⚠️ Password-protected files throw an error — remove protection first.

Use Case 3: PPT Content Extraction

60-page supplier pitch deck. Ask: "Read this PPT and summarize: 1) company background, 2) core tech, 3) pricing (if any)." Works well, but text inside images (screenshots of tables) is invisible — only direct text box content is readable.

Combining With Other Skills

+ translate-cli: Extract English doc content, then translate. Much cleaner than translating PDFs directly.

+ humanizer: After extracting and summarizing, run through humanizer to avoid AI-sounding outputs.

SFD Lab Usage

Three main workflows: supplier contract review (from "1 hour manual reading" to "5-minute AI pre-scan"), weekly report aggregation, and meeting minutes processing (extract action items → update task tracker).

SFD Lab Note

The value isn't that this skill is "powerful" — it's that it bridges a gap that previously required manual work. Every workflow that stalls on "file processing" is a candidate for this fix. If it saves even 30 minutes of copy-pasting daily, that's 15 hours per month recovered.