Skip to main content
skill CX Codex GP ChatGPT official · OpenAI

statistical-and-uncertainty-visualization — Codex skill: honest charts

Builds charts and dashboards that show spread, intervals and missing data instead of hiding them behind a single summary line.

Install into Codex · Skills CLI (Vercel) All methods and platforms ↓
npx skills add openai/plugins --skill statistical-and-uncertainty-visualization -a codex
Open on GitHub

What statistical-and-uncertainty-visualization does

Reach for this skill when the risk is analytical distortion, not rendering difficulty. It covers distributions, intervals, uncertainty, missingness, aggregation effects and the usual ways a chart misleads. The default assumption is blunt: if a claim depends on variability, estimation, sampling or model uncertainty, the visualization should show it.

The working pattern runs in four steps. First, figure out whether the viewer needs exact values, distributions, intervals or model-derived estimates. Then pick encodings that show spread, uncertainty, missingness and sample size honestly. Next, check that aggregation or smoothing has not summarized away the variation the decision depends on. Short explanations go next to the view when the uncertainty concept is not obvious. Reference files cover summary choices, uncertainty encodings, analytical pitfalls and missingness.

What you get back is the statistical question named in words, a reason the chosen encoding is more truthful than the tempting alternative, and a flag wherever aggregation or interval choice can mislead. The skill ships in the openai/plugins repository under the MIT license.

What it helps with

  • show spread instead of one average line
  • pick between histogram, box plot and density plot
  • draw confidence intervals without misleading readers
  • surface missing data and sample size on a dashboard
  • spot where aggregation eats the variation that matters

Example prompts for the agent

  • What chart should I use to show uncertainty in this data?
  • Should this be a histogram, box plot, violin plot, or density plot?
  • This dashboard hides variability. How should I fix it?

How to install statistical-and-uncertainty-visualization

1Skills CLI (Vercel)

npx skills add openai/plugins --skill statistical-and-uncertainty-visualization -a codex

2Manually: put the files in place

.agents/skills/statistical-and-uncertainty-visualization/SKILL.md

For all projects use ~/.agents/skills/

Step by step, with commands for each platform: Codex skills: how to install, where they live, how to call them

Questions about statistical-and-uncertainty-visualization

How do I install statistical-and-uncertainty-visualization in Claude?

Run npx skills add openai/plugins --skill statistical-and-uncertainty-visualization, then npx skills add openai/plugins --skill statistical-and-uncertainty-visualization -a codex. The skill file then sits at .agents/skills/statistical-and-uncertainty-visualization/SKILL.md.

What does statistical-and-uncertainty-visualization do?

It helps design charts and dashboards that show distributions, intervals, confidence, missingness and sampling effects honestly. The skill names the statistical question and explains why the chosen encoding is more truthful.

How is it different from generic chart advice?

It targets cases where the main risk is analytical distortion rather than rendering difficulty. Aggregation, smoothing and interval choice get called out as places where a chart can mislead.

Source text

SKILL.md · MIT
---
name: statistical-and-uncertainty-visualization
description: 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.
---

# 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

1. Identify whether the viewer needs exact values, distributions, intervals, or model-derived estimates.
2. Choose encodings that show spread, uncertainty, missingness, or sample size honestly.
3. Avoid summarizing away the variation that matters to the decision.
4. 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."

© OpenAI · MIT · openai/plugins

Similar skills

All skills for Data and databases →

From the same set304

The whole set →
vercel-firewall A skill that walks your agent through Vercel Firewall: custom WAF rules, IP blocks, rate limiting, Attack Mode and the vercel firewall CLI. CX Codex GP ChatGPT 12installs visualize-data This skill designs, revises, and checks quantitative charts. Use it when an analytical answer needs a clear, defensible visual. CX Codex GP ChatGPT 11installs accessibility-and-inclusive-visualization A Claude and Claude skill that reviews charts, diagrams and dashboards for accessibility: contrast, labels, keyboard paths, text alternatives. CX Codex GP ChatGPT 11installs audit Walks through product flows step by step, captures verified screenshots, and flags UX and accessibility issues in chat. CX Codex GP ChatGPT 10installs analyze-data-quality Evaluates whether datasets and metric tables are reliable enough for dashboards or models. Helps catch duplicates and anomalies. CX Codex GP ChatGPT 9installs typescript-data-visualization-engineering Guides typed data visualization architecture in TypeScript, covering data contracts, state boundaries, and renderer selection from D3 to WebGL. CX Codex GP ChatGPT 9installs gantt-chart-visualization Designs Gantt charts, audits schedule models, and selects frontend visualization stacks. Useful when task dates, milestones, and dependencies guide project plans. CX Codex GP ChatGPT 9installs canvas2d-data-visualization Renders data visualizations with Canvas2D when DOM overhead slows down the page. Designed for dense scatterplots, sparkline grids, heatmaps, and streaming traces. CX Codex GP ChatGPT 9installs

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor