GenOffice is an open-source office suite for editing Word, Excel, PowerPoint, PDF, and Markdown files with AI-assisted document editing. People use it as an alternative to Microsoft Office on macOS, Windows, and Linux.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add genspark-ai/genoffice --skill survey-analystgit clone --depth 1 https://github.com/genspark-ai/genofficeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/genspark-ai/genoffice/survey-analyst)<a href="https://agentmods.dev/skills/genspark-ai/genoffice/survey-analyst"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/survey-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/genspark-ai/genoffice/survey-analyst"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/survey-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.00808 |
| Opus 5.5 | $0.00014 | $0.00323 |
| Sonnet 5.5 | $0.00007 | $0.00162 |
| Haiku 4.5 | $0.00004 | $0.00081 |
Grade A, and why
survey-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a survey analyst. The user gives you raw survey responses (exported table, CSV or pasted text) and the questionnaire; you deliver a cleaned analysis workbook and a findings report.
Workflow
- Read the survey structure first: question types (single choice / multiple choice / scale / matrix / open-ended), sample size, demographic variables (gender / age / region / user type). Ask for the question wording when it is missing, otherwise option codes cannot be interpreted; also ask about the research purpose and the 2-3 questions the user most wants answered.
- Clean: drop responses with too-short completion time, straight-lining (the same option throughout) or logical contradictions (such as rating a purchase experience without having purchased), recording the exclusion rules and counts; split multiple-choice questions into 0/1 columns; align scale direction (reverse-scored items flipped); remove empty open-ended answers.
- Descriptive statistics: frequency and share per question; mean and Top-2 / Bottom-2 share for scale questions.
- Cross-tabulation: cross-tabs by the user's chosen demographic variables, highlighting share differences of 10 percentage points or more or clearly different means; groups under 30 respondents are marked "small sample, indicative only".
- Open-ended questions: group into 5-8 themes with counts, quoting 1-2 verbatim responses per theme as evidence.
- Build the workbook as an Excel workbook with the spreadsheet tools available here, titled " Analysis"; then build the report as a Word document with the document tools available here, titled " Findings Report".
Workbook structure
- Sheet "Cleaned data": the cleaned detail plus an exclusion flag column.
- Sheet "Cleaning log": Rule / Excluded / Remaining sample.
- Sheet "Per-question stats": frequency, share and mean per question, computed with formulas (COUNTIF / AVERAGE), never typed.
- Sheet "Cross-tabs": pivot-style cross-tables, groups as rows, options as columns.
- Sheet "Open-ended": Theme / Count / Example quote.
- Charts for key questions: bar for single choice, stacked bar for scales, clustered column for group comparisons.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 48 lines · 36 tokens per session scan A 990f782dff6f
survey-analyst is a skill published in the GitHub repository genspark-ai/genoffice (10,762 stars, last pushed yesterday), licensed Apache-2.0. It adds 36 tokens to every session and 808 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-23.
Other skills, from other repositories
gsheets
Google Sheets via MCP — read, write, create, list, share spreadsheets. Use when reading, writing, or managing Google Sheets data.
xlsx
Working with Excel files programmatically.
CSV / Spreadsheet Operations
List sheets, read rows, read a single line, and write back to spreadsheets. Supports .csv / .tsv / xlsx / Google Sheets. Canonical partner for agentbatch when iterating row-by-row.
data-analysis
Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data.
excel-analyzer
Excel deep analysis - formula audit, data validation, pivot summaries.
office-router
Route Office requests into the correct xlsx, docx, or pptx workflow, while preferring Slidev for new presentation drafts unless .pptx is explicitly required.