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Data Storyteller

Checked
dkyazzentwatwa·vlatest·data

Transforms complex data into engaging, narrative-driven stories with visualizations for clear understanding and impactful insights.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add dkyazzentwatwa/chatgpt-skills --skill data-storyteller -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

dkyazzentwatwa

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned dkyazzentwatwa/chatgpt-skills at 103b4308f6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
103b4308f6
Manifest
data-storyteller/SKILL.md
Scanned
16 files, 7,655 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Data Storyteller skill transforms complex data from CSV or spreadsheet files into engaging, narrative-driven reports with visualizations. It consolidates several analytics helpers including audit, comparison, statistics, pivot tables, experiment analysis, and time series decomposition. The tool translates these analyses into clear findings, risks, and recommended next actions for improved understanding and impactful insights. This skill is designed to be the primary analytics tool for structured data.

When to use it

  • Creating executive summaries and narrative reports from CSV or spreadsheet data.
  • Performing data quality audits, comparisons, and anomaly reviews.
  • Analyzing statistical data, pivoting tables, experiment results, ROI, and budgets.
  • Summarizing survey responses and performing time-series decomposition.

Key capabilities

  • Data profiling (shape, column types, missing values)
  • Data quality auditing
  • Dataset comparison
  • Correlation exploration
  • Outlier detection
  • Statistical analysis
  • Survey summarization
  • Time series decomposition
  • Pivot table generation
  • A/B test calculation
  • ROI and budget analysis

Example prompts

  • "Create an executive summary report from this CSV file."
  • "Perform a data quality audit on this spreadsheet and highlight any issues."
  • "Analyze the survey results and provide a narrative summary of key findings."

Tips & gotchas

  • Start with scripts/data_storyteller.py for cohesive reports, or use focused helper scripts (e.g., data_quality_auditor.py) for narrow tasks.
  • Be mindful of the guardrails: avoid overstating causal claims from correlations and always call out data quality problems upfront.
  • Keep executive summaries concise and move detailed methodology behind them.