csv-analysis

A guide for analysing local CSV files, which are tables stored as text with rows and columns. It covers checking the data, calculating grouped results and rates, creating charts, and writing a short Markdown report.

In plain words
What is it for?
Use it to inspect columns and row counts, calculate aggregates or rates, make charts, and document findings.
Why use it?
It provides a repeatable way to turn raw CSV data into checked results and a readable summary.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/zjunlp/datamind/csv-analysis
Any agent
npx skills add zjunlp/DataMind --skill csv-analysis
Clone the repo
git clone --depth 1 https://github.com/zjunlp/DataMind

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 333 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00044 $0.00333
Opus 5 $0.00022 $0.00167
Sonnet 5 $0.00009 $0.00067
Haiku 4.5 $0.00004 $0.00033

Measured 2d ago against content hash 4f0574e10a1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

csv-analysis 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.

datacope/general/docs/skills-example/csv-analysis/SKILL.md · 56 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 56 lines · 44 tokens per session scan A 4f0574e10a1b

Subscribe to this mod's changes

csv-analysis is a skill published in the GitHub repository zjunlp/DataMind (135 stars, last pushed 3d ago), with no licence file. It adds 44 tokens to every session and 333 once invoked, about $0.0002 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 2026-08-30.

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