data-analyst

data-analyst is a skill for Claude Code, Codex from genspark-ai/genoffice. It costs 24 tokens per session (320 once invoked), scanned A, original, Apache-2.0.

A data-analysis workflow that turns raw information into a cleaned Excel workbook with formulas, charts, and plain-language findings. It checks fields, row counts, missing values, duplicates, and inconsistent units before analysis.

In plain words
What is it for?
Use it to prepare cleaned detail sheets, summary statistics, comparisons over time, Top-N lists, charts, and three to five evidence-based conclusions.
Why use it?
It removes the need to clean data, calculate summaries, and explain the results separately. It also helps avoid unsupported conclusions by saying when the data is insufficient.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to prepare cleaned detail sheets, summary statistics, comparisons over time, Top-N lists, charts, and three to five evidence-based conclusions.

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Install with agentmods
npx agentmods add skills/genspark-ai/genoffice/data-analyst
About the project

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.

genspark-ai/genoffice · 10,762 stars · on GitHub · genoffice.ai

Install

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.

Any agent
npx skills add genspark-ai/genoffice --skill data-analyst
Clone the repo
git clone --depth 1 https://github.com/genspark-ai/genoffice

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for data-analyst

README.md
[![agentmods](https://agentmods.dev/badge/skills/genspark-ai/genoffice/data-analyst/github.svg)](https://agentmods.dev/skills/genspark-ai/genoffice/data-analyst)
Your own site
<a href="https://agentmods.dev/skills/genspark-ai/genoffice/data-analyst"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/data-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.

agentmods 80×15 button for data-analyst

Your own site · 80×15
<a href="https://agentmods.dev/skills/genspark-ai/genoffice/data-analyst"><img src="https://agentmods.dev/badge/skills/genspark-ai/genoffice/data-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 320 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.00320
Opus 5.5 $0.00010 $0.00128
Sonnet 5.5 $0.00005 $0.00064
Haiku 4.5 $0.00002 $0.00032

Measured 2d ago against content hash 9f16f81548d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-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.

skills/recommended/data-analyst/SKILL.md · 22 lines

What it actually says

You are a data analyst. The goal is for a non-technical user to come away with insights they can understand, not just a table.

Workflow

  1. Look at the data first: read the attachment or pasted data once through, confirm what each field means, the row count, and obvious dirty data (blanks / duplicates / inconsistent units). Ask about anything ambiguous before going on.
  2. Build the workbook as an Excel workbook with the spreadsheet tools available here.
    • Sheet 1 holds the cleaned detail (units and date formats unified, with a note of what was excluded);
    • Sheet 2 holds the summary: grouped statistics, period-on-period and year-on-year comparisons and Top-N, all with formulas, never typed results;
    • Key metrics get charts (line for trends, bar / pie for composition); headers bold, number columns right-aligned.
  3. Once the workbook is done, give 3-5 conclusions in the reply, each = observation + figure + likely explanation or recommendation. Do not restate the table.
  4. Where the data cannot support a conclusion, say "insufficient data" rather than over-inferring.
Changes

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.

  1. 2d ago First seen · 22 lines · 24 tokens per session scan A 9f16f81548d4

Subscribe to this mod's changes

data-analyst is a skill published in the GitHub repository genspark-ai/genoffice (10,762 stars, last pushed yesterday), licensed Apache-2.0. It adds 24 tokens to every session and 320 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.