LobsterAI is an open-source desktop AI agent that operates files, commands, browsers, documents, spreadsheets, slides, messaging channels, and scheduled jobs in a user's working environment. It supports office work, research, and custom multi-agent workflows, while catalogue add-ons extend the agent with additional skills and workflows.
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 netease-youdao/LobsterAI --skill xlsxgit clone --depth 1 https://github.com/netease-youdao/LobsterAIWrote 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/netease-youdao/lobsterai/xlsx)<a href="https://agentmods.dev/skills/netease-youdao/lobsterai/xlsx"><img src="https://agentmods.dev/badge/skills/netease-youdao/lobsterai/xlsx/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/netease-youdao/lobsterai/xlsx"><img src="https://agentmods.dev/badge/skills/netease-youdao/lobsterai/xlsx.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 99 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00096 | $0.02749 |
| Opus 5.5 | $0.00038 | $0.01100 |
| Sonnet 5.5 | $0.00019 | $0.00550 |
| Haiku 4.5 | $0.00010 | $0.00275 |
Grade A, and why
xlsx 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 10d 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.
This is a copy
81% identical to xlsx — 42 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requirements for Outputs
All Excel files
Zero Formula Errors
- Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)
Preserve Existing Templates (when updating templates)
- Study and EXACTLY match existing format, style, and conventions when modifying files
- Never impose standardized formatting on files with established patterns
- Existing template conventions ALWAYS override these guidelines
Financial models
Color Coding Standards
Unless otherwise stated by the user or existing template
Industry-Standard Color Conventions
- Blue text (RGB: 0,0,255): Hardcoded inputs, and numbers users will change for scenarios
- Black text (RGB: 0,0,0): ALL formulas and calculations
- Green text (RGB: 0,128,0): Links pulling from other worksheets within same workbook
- Red text (RGB: 255,0,0): External links to other files
- Yellow background (RGB: 255,255,0): Key assumptions needing attention or cells that need to be updated
Number Formatting Standards
Required Format Rules
- Years: Format as text strings (e.g., "2024" not "2,024")
- Currency: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
- Zeros: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
- Percentages: Default to 0.0% format (one decimal)
- Multiples: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)
- Negative numbers: Use parentheses (123) not minus -123
Formula Construction Rules
Assumptions Placement
- Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells
- Use cell references instead of hardcoded values in formulas
- Example: Use =B5*(1+$B$6) instead of =B5*1.05
Formula Error Prevention
- Verify all cell references are correct
- Check for off-by-one errors in ranges
- Ensure consistent formulas across all projection periods
- Test with edge cases (zero values, negative numbers)
- Verify no unintended circular references
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago Changed · +2 lines f8f49b5dae91
- 1mo ago First seen · 290 lines · 96 tokens per session scan A 14e2afb42cf6
xlsx is a skill published in the GitHub repository netease-youdao/LobsterAI (6,150 stars, last pushed yesterday), licensed MIT. It adds 96 tokens to every session and 2,749 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 81% identical to xlsx, differing in 42 lines, and is treated as a copy.
Other skills, from other repositories
ha-data-analytics
A local-first data-analysis and reporting skill for CSV and spreadsheet files. It produces decision-ready analyses and shareable offline reports while separating facts, calculations, interpretations, and recommendations.
office-xlsx
Use when the user asks to create, inspect, verify, analyze, format, or deliver Excel .xlsx workbooks, Google Sheets-targeted spreadsheet artifacts, trackers, budgets, models, tables, dashboards, formulas, CSV/TSV-to-XLSX conversions, or spreadsheet-ready data packs.
sn-da-excel-workflow
A step-by-step workflow for analysing Excel workbooks with multiple sheets. It covers reading data, cleaning it, filtering and combining results, and exporting reports, with a separate strategy for large files.
sn-da-large-file-analysis
A workflow for analyzing very large Excel datasets, especially files with at least 10,000 rows. It uses lower-memory reading, streaming through rows, splitting work into chunks, and converting data to Parquet, a column-based data format suited to repeated analysis.
category-filtering-and-difficulty-analysis
A workflow for grouping Excel records into categories and analyzing them across several measures, including text length and terminology density.
multi-sheet-reading-and-analysis
A workflow for reading and analyzing Excel files with multiple worksheets, including data cleaning, grouping, fitting lines to data, and formatted charts.