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 w95/awesome-claude-corporate-skills --skill csv-data-summarizergit clone --depth 1 https://github.com/w95/awesome-claude-corporate-skillsWrote 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/w95/awesome-claude-corporate-skills/csv-data-summarizer)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/csv-data-summarizer"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/csv-data-summarizer/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/w95/awesome-claude-corporate-skills/csv-data-summarizer"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/csv-data-summarizer.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 | $0.00025 | $0.01262 |
| Opus 5 | $0.00013 | $0.00631 |
| Sonnet 5 | $0.00005 | $0.00252 |
| Haiku 4.5 | $0.00003 | $0.00126 |
Grade A, and why
csv-data-summarizer 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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- csv-data-summarizer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CSV Data Summarizer
This Skill analyzes CSV files and provides comprehensive summaries with statistical insights and visualizations.
When to Use This Skill
Claude should use this Skill whenever the user:
- Uploads or references a CSV file
- Asks to summarize, analyze, or visualize tabular data
- Requests insights from CSV data
- Wants to understand data structure and quality
How It Works
⚠️ CRITICAL BEHAVIOR REQUIREMENT ⚠️
DO NOT ASK THE USER WHAT THEY WANT TO DO WITH THE DATA. DO NOT OFFER OPTIONS OR CHOICES. DO NOT SAY "What would you like me to help you with?" DO NOT LIST POSSIBLE ANALYSES.
IMMEDIATELY AND AUTOMATICALLY:
- Run the comprehensive analysis
- Generate ALL relevant visualizations
- Present complete results
- NO questions, NO options, NO waiting for user input
THE USER WANTS A FULL ANALYSIS RIGHT AWAY - JUST DO IT.
Automatic Analysis Steps:
The skill intelligently adapts to different data types and industries by inspecting the data first, then determining what analyses are most relevant.
-
Load and inspect the CSV file into pandas DataFrame
-
Identify data structure - column types, date columns, numeric columns, categories
-
Determine relevant analyses based on what's actually in the data:
- Sales/E-commerce data (order dates, revenue, products): Time-series trends, revenue analysis, product performance
- Customer data (demographics, segments, regions): Distribution analysis, segmentation, geographic patterns
- Financial data (transactions, amounts, dates): Trend analysis, statistical summaries, correlations
- Operational data (timestamps, metrics, status): Time-series, performance metrics, distributions
- Survey data (categorical responses, ratings): Frequency analysis, cross-tabulations, distributions
- Generic tabular data: Adapts based on column types found
-
Only create visualizations that make sense for the specific dataset:
- Time-series plots ONLY if date/timestamp columns exist
- Correlation heatmaps ONLY if multiple numeric columns exist
- Category distributions ONLY if categorical columns exist
- Histograms for numeric distributions when relevant
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.
- 7d ago First seen · 150 lines · 25 tokens per session scan A 1599338ac2db
csv-data-summarizer is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (195 stars, last pushed 6mo ago), licensed MIT. It adds 25 tokens to every session and 1,262 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
Other skills, from other repositories
steuer-assistent
Points to the standalone module steuer-assistent: a local, offline-first receipt worksheet for German employee income-related expenses (Werbungskosten) -- record, sum to the cent, private ZIP export. Use this skill when Werbungskosten receipts should be prepared in a structured way -- with a clear boundary: not tax…
monthly-close-checklist-and-reconciliation-prep
A bookkeeping preparation skill that turns a pasted bank export or transaction list into a monthly-closing checklist, draft categories with disputed items marked, and a summary for an accountant or investor.
survey-results-analyzer
Analyze survey CSV files and extract quantitative frequencies, qualitative themes, and Top-3 insights. No Python required — Cowork-native. Use when reviewing Google Forms/Typeform/SurveyMonkey exports, preparing stakeholder reports, or turning raw survey data into actionable findings. Triggers: 'analyze survey…
xlsx
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify…
xlsx
Create, read, edit, and fix spreadsheets — add columns, compute formulas, format cells, generate charts, and clean messy tabular data.
xlsx
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or…