ppw:visualization
Recommend appropriate chart types for experimental data with rationale and tool hints. 为实验数据推荐合适的图表类型，支持地理空间数据可视化建议。
npx skills add majiayu000/claude-skill-registry --skill ppw-visualization --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Purpose This Skill accepts a plain-language description of experimental data (data type, key variables, sample size) and a research question (what the figure must communicate), then recommends 2–3 chart types ordered by fit. Each recommendation includes the chart type name, a 1–2 sentence rationale referencing the user's specific data and question, and Python/R library hints (names only, no code blocks). The Skill is geography-aware: if the data description contains spatial signals (coordinates, regions, administrative boundaries, GIS data), it proactively includes choropleth maps, spatial scatter plots, or kernel density maps as candidates alongside general types. When no spatial signals are present, only general chart types are recommended — geography charts are never forced onto non-spatial data. The Skill accepts text descriptions only; it does not read or process actual data files. ## Core Prompt > Source: [awesome-ai-research-writing](https://github.com/Leey21/awesome-ai-research-writing) — 实验绘图推荐 ````markdown # Role 你是一位就职于顶级科学期刊（如 Nature, Science）或计算机顶级会议（如 CVPR, NeurIPS）的资深数据可视化专家。你拥有极高的学术审美，严谨且专业。你擅长从学术界最认可的标准图表库中，挑选最能证明实验有效性的绘图方案，并能针对特殊的数据分布提出巧妙的视觉补救措施。 # 标准学术图表库 在推荐前
- Purpose
- Core Prompt
- Trigger
- Modes
- References
- Required (always loaded)
- Leaf Hints
- Ask Strategy
- Workflow
- Step 0: Workflow Memory Check
- Step 1 — Collect Context
- Step 2 — Detect Spatial Signals and Select Chart Candidates
- Step 3 — Generate Recommendation Cards
- Output Contract
What does the ppw:visualization skill do?
Recommend appropriate chart types for experimental data with rationale and tool hints. 为实验数据推荐合适的图表类型，支持地理空间数据可视化建议。
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ppw-visualization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.