Data visualisation

Audits a dashboard for decision usefulness, metric definitions, clutter, misleading visuals and staleness, ending in a ranked redesign shortlist. Use when a dashboard is ignored or distrusted.

Builds a self-contained HTML dashboard from a CSV with a script, a chart per question, filters and accessible colours, and checks every number against the data. Use for a quick, shareable dashboard.

Plans a Looker Studio report with data sources, credentials, blends, calculated fields, pages, controls and performance settings, ready to build step by step. Use before building a shared dashboard.

Rules for any chart the assistant designs or codes, covering one message, an action title, honest axes, direct labels, accessible colour and a source note. Load whenever a chart or plot is made.

Chooses accessible categorical, sequential or diverging chart palettes with hex codes, colour-vision and contrast checks and highlight rules, fitted to brand colours. Use when colouring charts.

Recommends the chart that best carries a specific message for a given data shape, with encodings, the alternatives considered and the anti-patterns to avoid. Use before building a chart.

Critiques a chart for clarity, honesty (axes, scales, cherry-picked ranges) and accessibility, and proposes a concrete redesign. Use before a chart goes into a deck, report or dashboard.

Builds a dashboard in gated steps from decisions and users to metric definitions, data checks, a wireframe, a build spec and a QA and adoption review. Use when a dashboard must be trusted and used.

Data visualisation designer who starts from the message and the reader, picks honest encodings, strips clutter and annotates what matters. Use for any chart, dashboard or data graphic.

Writes short alt text, a structured long description and a data table for a chart so screen-reader users get the same insight as sighted readers. Use when publishing charts on the web or in documents.

Designs a KPI dashboard from the decisions it must support, covering audience, questions, metric definitions, one chart per question, filters and layout. Use before building it in a BI tool.

Designs a readable data table for a report or slide, covering what to include, ordering, number formats, alignment, highlighting and footnotes. Use when your tables get skipped or misread.

Designs a map for the data at hand (choropleth, dot, proportional symbol, hex bin or flow) with normalisation, classification, colour, projection and pitfalls. Use before putting data on a map.

Draws a process as a valid Mermaid flowchart, swimlane or sequence diagram with decisions, owners and exceptions, and lists the gaps in the description. Use to document how a process works today.

Explains in plain words what a chart shows, what it does not show, how it might mislead and what to ask about it. Use when you are handed a chart in the news, a report or a meeting.

Builds data literacy with a round-by-round quiz on reading charts, from axes and scales to misleading designs, using described or uploaded charts and explaining every answer.

Turns analysis findings into a data story with one message, a sequence of charts with action titles and annotations, and the narrative linking them. Use when presenting to non-analysts.

Extracts the numbers from a passage of prose into a clean, sourced table, flags values that are not comparable, and recommends the chart that carries the message. Use with reports, articles or emails.

Writes publication-quality plotting code from data and intent, with labelled axes, accessible colours and an annotation on the key point. Use for matplotlib, seaborn, plotly, ggplot2 or Vega-Lite.

Writes Tableau calculated fields, LOD expressions and table calculations from plain-language definitions, with filter-order notes and test values. Use when building or fixing a Tableau workbook.