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Statistical And Uncertainty Visualization Skill for Codex

Design statistically honest and uncertainty-aware visualizations. Use when the user needs help showing distributions, intervals, confidence, missingness, sampling effects, or analytical rigor in charts and dashboards.

1k tokens
context cost
the whole folder, loaded on every use
6
files
instructions only
0
copies elsewhere
how many repositories repackaged it
4915
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/openai/plugins --skill statistical-and-uncertainty-visualization

What comes with it

3 671 bytes besides the instruction
agents/openai.yaml
references/distribution-and-summary-choices.md
references/experimental-and-analytical-pitfalls.md
references/missingness-and-confidence.md
references/uncertainty-encodings.md

The instruction itself

6 sections, as written by the author

Statistical and Uncertainty Visualization

Overview

Use this skill when the risk is analytical distortion rather than rendering difficulty. This skill focuses on distributions, intervals, uncertainty, missingness, aggregation effects, and common statistical storytelling failures.

Default assumption: if a claim depends on variability, estimation, sampling, or model uncertainty, the visualization should show that explicitly.

Working Pattern

  • Identify whether the viewer needs exact values, distributions, intervals, or model-derived estimates.
  • Choose encodings that show spread, uncertainty, missingness, or sample size honestly.
  • Avoid summarizing away the variation that matters to the decision.
  • Pair concise explanations with the view when the uncertainty concept is nontrivial.

Output Expectations

  • Name the statistical question, not just the chart type.
  • Explain why the chosen encoding is more truthful than the tempting alternative.
  • Call out when aggregation, smoothing, or interval choice can mislead.

References

  • Shared theory:
  • ../../references/foundations/task-abstraction-and-chart-selection.md
  • ../../references/foundations/perception-color-and-encoding.md
  • Skill references:
  • ./references/distribution-and-summary-choices.md
  • ./references/uncertainty-encodings.md
  • ./references/experimental-and-analytical-pitfalls.md
  • ./references/missingness-and-confidence.md

Representative Prompts

  • "What chart should I use to show uncertainty here?"
  • "Should this be a histogram, box plot, violin plot, or density plot?"
  • "How do I show confidence intervals without misleading people?"
  • "This dashboard hides variability. How should I fix it?"
  • "Help me visualize missing data and sample size honestly."

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How to use it

Copy the folder

Take openai/statistical-and-uncertainty-visualization from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.