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data-analysis-notebook

data-analysis-notebook is a skill for Claude Code, Codex from CodeInfinity1/Stram. It costs 28 tokens per session (468 once invoked), scanned A, original, MIT.

A notebook-like workflow for analyzing local CSV or JSON data with Python and saving reproducible results. It can support calculations, simulations, file parsing, and small plots.

In plain words
What is it for?
Use it to inspect CSV structure, explore data, calculate results, run experiments, and create analysis artifacts or notes.
Why use it?
It keeps data analysis bounded and repeatable, while recording assumptions, run details, and output files.

Skill for Claude CodeCodex

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

not rated 11repo 2mo ago A scan 28 tokens original MIT

Good fit Use it to inspect CSV structure, explore data, calculate results, run experiments, and create analysis artifacts or notes.

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Install with agentmods
npx agentmods add skills/codeinfinity1/stram/data-analysis-notebook
View source ↗ CodeInfinity1/Stram
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 CodeInfinity1/Stram --skill data-analysis-notebook
Clone the repo
git clone --depth 1 https://github.com/CodeInfinity1/Stram

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-analysis-notebook

README.md
[![agentmods](https://agentmods.dev/badge/skills/codeinfinity1/stram/data-analysis-notebook/github.svg)](https://agentmods.dev/skills/codeinfinity1/stram/data-analysis-notebook)
Your own site
<a href="https://agentmods.dev/skills/codeinfinity1/stram/data-analysis-notebook"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/data-analysis-notebook/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-analysis-notebook

Your own site · 80×15
<a href="https://agentmods.dev/skills/codeinfinity1/stram/data-analysis-notebook"><img src="https://agentmods.dev/badge/skills/codeinfinity1/stram/data-analysis-notebook.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 468 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 $0.00028 $0.00468
Opus 5.5 $0.00011 $0.00187
Sonnet 5.5 $0.00006 $0.00094
Haiku 4.5 $0.00003 $0.00047

Measured 1mo ago against content hash 486dc1056d9f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-analysis-notebook 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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/profile_csv.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/office-productivity/data-analysis-notebook/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Analysis Notebook

Purpose

Use the native Python interpreter as a notebook-like analysis environment. The goal is reproducible, bounded analysis with artifacts and clear assumptions.

When To Use

Use for data exploration, CSV/JSON analysis, calculations, simulations, small plots, file parsing, and technical experiments.

Inputs And Evidence

  • Data path, question, allowed imports, output artifacts, and success criteria.
  • Interpreter run IDs, manifests, stdout/stderr, and artifacts.

Tool Map

  • csv_dataset_profile
  • python_interpreter
  • python_interpreter_runs
  • python_interpreter_run
  • python_interpreter_artifact
  • read_file
  • write_note
  • agent_skill_script_catalog
  • agent_skill_script_run

Native Scripts

  • scripts/profile_csv.py: profiles a CSV file with columns, sampled rows, missing counts, and simple numeric ranges using the Python standard library.

Workflow

  1. Define the analysis question and data boundaries.
  2. Use csv_dataset_profile first for CSV structure, missing values, numeric ranges, and sample rows.
  3. Choose the least-privilege interpreter sandbox/import mode only when native analysis tools are insufficient.
  4. Run small, readable analysis code.
  5. Inspect stdout, errors, and artifacts.
  6. Iterate only as needed.
  7. Summarize methods, results, assumptions, and reproducibility.

Native Implementation Boundaries

  • Use Stram python_interpreter tools.
  • Do not import external reference Jupyter live-kernel code.
  • CSV profiling is native; notebook/live-kernel support beyond this requires native implementation.

Safety And Approval

  • Interpreter execution is approval-gated.
  • Keep network/subprocess/import permissions minimal.
  • Do not expose sensitive data in outputs.

Verification

  • Report run IDs and artifacts.
  • Validate calculations with sanity checks.
  • Note if packages were unavailable.

Failure Modes

  • Running code without a clear question.
  • Trusting a single output without sanity checks.
  • Losing reproducibility.

Read the full file on GitHub · 74 lines

Files

What ships with it

1 file 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.

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. 1mo ago First seen · 74 lines · 28 tokens per session scan A 486dc1056d9f

Subscribe to this mod's changes

data-analysis-notebook is a skill published in the GitHub repository CodeInfinity1/Stram (11 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 468 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 2026-09-03.

Analytics and metricsai-agentai-agentsai-toolsdesktop-automationdesktop-automation-softwaredesktop-automation-windows
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