| name | seaborn |
| description | Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization. |
| source_skill_id | k-dense-ai-scientific-agent-skills-scientific-skills-seaborn-skill-md |
| category | Science, research & data analysis |
| source_mirror | ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/seaborn/SKILL.md |
| benchmark_status | artifact_gated |
seaborn
Use this skill when the task matches the description above or the source path clearly applies. Start with this concise entrypoint; open ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/seaborn/SKILL.md only when implementation details, commands, assets, or references are needed.
Workflow
- Confirm the task matches this skill's scope.
- Read the local source mirror if more detail is required.
- Follow repository-level
AGENTS.md; use one AI session only.
- Keep claims tied to files, commands, citations, or benchmark artifacts.
Verification
- Source mirror:
../../../../../skills/by-category/science-research-data-analysis/latest-release-community/seaborn/SKILL.md
- Source commit:
eb20fb0dcb0b1dadaa3db2737188f0755bbc4770
- Static benchmark results: see
docs/benchmark-results.md
- Runtime artifacts recorded by this entrypoint:
0
- Assigned scenarios:
skill-proof-k-dense-ai-scientific-agent-skills-scientific-skills-seaborn-skill-md, science-research-and-data-analysis-cellxgene-census, science-research-and-data-analysis-chembl, science-research-and-data-analysis-ome-ngff-samples
Do not claim this skill passed a runtime benchmark until a validated artifact exists.
