Data Visualization Selector

Select the correct graphic type (table, bar chart, line graph) for a dataset and rhetorical goal, then design and frame it to communicate evidence clearly and honestly. Use this skill whenever the user needs to present quantitative data in a research paper, report, thesis, presentation, or professional document and asks: which chart should I use, how should I visualize this data, how do I make this graphic clearer, is my chart misleading, how do I label or title a table or figure, or how do I introduce a graphic in text. Also triggers on: "my advisor said the table is confusing," "should I use a bar chart or line graph," "how do I make readers see my point in this figure," "is this graph ethical," "my chart looks amateurish," "the scale on my graph looks off," or any request to improve the visual communication of numerical evidence. Covers the full workflow: verbal-vs-visual decision → graphic type selection based on rhetorical effect → design simplification → framing with title, intro sentence, and labels → ethical integrity checks.

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Install

Claude CodeClawhHubnpxCursorCodexGemini CLI

1. Add marketplace

› /plugin marketplace add bookforge-ai/bookforge-skills

2. Install plugin

› /plugin install the-craft-of-research@bookforge-skills

3. Use the skill

› /data-visualization-selector

CC-BY-SA · Open sourceGitHub

Source Book

The Craft of Research, Fourth Edition

Wayne C. Booth, Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald

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Revise dense, unclear prose into clear, readable sentences by applying four diagnostic principles — characters-as-subjects, actions-as-verbs, old-before-new information flow, and complexity-last sentence endings. Use this skill whenever the user shares a draft passage, paragraph, or document and asks you to make it clearer, more readable, easier to follow, less dense, less academic-sounding, or better written — even if they don't use those words. Also triggers on: "can you revise this," "this feels clunky," "my advisor said this is unclear," "make this flow better," "my writing sounds stilted," or any request to improve prose style in research papers, reports, essays, grant proposals, or professional documents. Apply all four principles end-to-end; return a revised version with brief annotations showing what changed and why.

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Build a complete, structured research argument from a framed problem — assembling all five elements (claim, reasons, evidence, acknowledgment/response, warrant) using the Claim→Reason→Evidence chain. Use this skill when the user has a research problem or framed question and needs to construct the supporting argument that justifies their answer, has a working thesis or claim but does not know how to assemble the reasons and evidence that make it hold, needs to identify which of the five claim types (fact, definition, cause, evaluation, policy) their main claim is and what kind of evidence each type demands, wants to evaluate whether their claim is specific and significant enough to anchor an argument, cannot tell whether a statement is a reason or evidence and keeps treating soft generalizations as hard data, has evidence but cannot determine whether it meets the quality standards (accurate, precise, sufficient, representative, authoritative) their readers will apply, needs to plan their argument visually using a storyboard (claim + reasons + evidence cards) before drafting, or wants to thicken a thin argument by identifying where acknowledgments and warrants are needed. This is the hub skill for research argumentation — use it before counterargument-handler (which handles detailed acknowledgment/response), warrant-tester (which tests whether reasons are genuinely relevant to claims), and research-paper-planner (which turns the completed argument structure into a paper outline).

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