statistical-and-uncertainty-visualization Skill
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. Published by openai in plugins.
Decision snapshot
Is this a fit?
Design and media, Includes SKILL.md, Reusable instructions
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
20 days ago
No specific cautions were detected. Review the source and requested permissions before installing.
What is statistical-and-uncertainty-visualization Skill?
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. Published by openai in plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Design and media
- Design and media use cases
Declared skill metadata
- Source file: plugins/build-web-data-visualization/skills/statistical-and-uncertainty-visualization/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use statistical-and-uncertainty-visualization Skill
- Use it for design and media.
Built with
Editorial notes
Source
- Creator: openai
- Repository: openai/plugins
- Skill file: plugins/build-web-data-visualization/skills/statistical-and-uncertainty-visualization/SKILL.md
What it does
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.
Skill instructions
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 inte
Verified compatibility and discovery
Frequently asked questions
What is statistical-and-uncertainty-visualization?
statistical-and-uncertainty-visualization is a open-source AI agent skill with Copy skill directory. Design statistically honest and uncertainty-aware visualizations.
Who is statistical-and-uncertainty-visualization best for?
statistical-and-uncertainty-visualization is best for reusing agent instructions, scripts, and references, design and media workflows.
How do I install statistical-and-uncertainty-visualization?
Install or run statistical-and-uncertainty-visualization using Copy skill directory. Check statistical-and-uncertainty-visualization for the latest setup command.
Is statistical-and-uncertainty-visualization actively maintained?
statistical-and-uncertainty-visualization may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
