Data Viz Narrative Writer
What This Skill Does
Writes the explanatory text that accompanies a data visualization — the headline, the introductory sentence, and the annotation or caption that tells readers what to look for and why it matters.
When To Use This Skill
- You have a finished chart, graph, or table and need text that guides the reader to the key finding rather than leaving them to interpret the data alone
- Your data visualization will appear in a digital article, a print spread, or a broadcast graphic, and you need concise, plain-English framing
- The chart is complex (multiple data series, long time range, unfamiliar units) and you need annotation text to prevent misreading
- You are working on a data journalism piece and need the narrative layer to connect the visual to the broader story argument
What You Need To Provide
Required:
- A description of the chart or table (what type it is, what it shows, what the axes or columns represent)
- The key finding — the single most important thing the data shows
- The data source and time period covered
Optional:
- The audience (general public, specialist readers, policymakers)
- Any important caveats about the data (methodology limits, missing data, definitional changes over time)
- The tone of the surrounding article (investigative, explanatory, neutral news, opinion)
- Word count target for the narrative text
How the Assistant Approaches This
- Identifies the single most significant finding in the data as described — the peak, the gap, the trend reversal, the unexpected comparison — and treats that as the headline finding
- Drafts a chart headline (also called a "active headline" or "tells headline") that states the finding rather than just labeling the chart topic
- Writes an introductory sentence of one to two lines that contextualizes the finding for a reader who may not examine the chart closely
- Produces annotation text or a caption that directs attention to the specific element of the chart that carries the main finding, and notes any caveats the reader needs to interpret the data accurately
Output Format
Three distinct text elements, clearly labeled:
Chart headline: One sentence, active voice, states the finding (e.g., "Rental costs in mid-sized cities outpaced wage growth every year from 2018 to 2025"). Maximum 12 words.
Introductory sentence: One to two sentences placed above or beside the chart. Tells the reader what to look for and why it matters. Plain English, no jargon, no hedge language unless the data genuinely requires it.
Caption / annotation: One to three sentences below or beside the chart. Notes the data source, the time period, any methodological caveats, and — if space allows — a secondary observation from the data.
Quality Criteria
Example
Input
Chart type: Line chart
What it shows: Annual average rent for a two-bedroom apartment in twelve mid-sized cities, compared to median annual wage growth, from 2016 to 2025
Key finding: From 2020 onwards, rent increases outpaced wage growth in ten of the twelve cities, with the gap widest in 2023
Data source: National Housing Survey, Office of Labor Statistics (both public datasets)
Time period: 2016–2025
Audience: General news readers
Caveats: Data covers formal rental market only; short-term rentals excluded
Tone: Neutral news
Output
Chart headline: Rents raced ahead of wages in most mid-sized cities after 2020
Introductory sentence: In ten of twelve cities tracked, the cost of renting a two-bedroom apartment grew faster than the typical worker's annual pay rise every year from 2020 to 2025 — with 2023 marking the widest gap on record.
Caption: Source: National Housing Survey and Office of Labor Statistics, 2016–2025. Figures cover the formal rental market; short-term and informal rentals are not included. Wage growth figures reflect median annual change across all full-time workers in each city.
Known Limitations
- This skill works from your description of the chart — it cannot read an image or a data file directly. The quality of the output depends on how precisely you describe the key finding and what the axes represent.
- For charts with multiple competing findings (e.g., some metrics up, some down), you must specify which finding is primary; otherwise the assistant will choose, and it may not be the one your story argument requires.
- Annotation text for highly technical data (epidemiological rates, financial derivatives, scientific measurements) should be reviewed by a subject-matter expert before publication.
Related Skills
1---2name: data-viz-narrative-writer3description: Writes the explanatory text that accompanies a data visualization — the headline, the introductory sentence, and the annotation or caption that tells readers what to look for and why it matters.4---5# Data Viz Narrative Writer67## What This Skill Does8Writes the explanatory text that accompanies a data visualization — the headline, the introductory sentence, and the annotation or caption that tells readers what to look for and why it matters.910## When To Use This Skill11- You have a finished chart, graph, or table and need text that guides the reader to the key finding rather than leaving them to interpret the data alone12- Your data visualization will appear in a digital article, a print spread, or a broadcast graphic, and you need concise, plain-English framing13- The chart is complex (multiple data series, long time range, unfamiliar units) and you need annotation text to prevent misreading14- You are working on a data journalism piece and need the narrative layer to connect the visual to the broader story argument1516## What You Need To Provide17**Required:**18- A description of the chart or table (what type it is, what it shows, what the axes or columns represent)19- The key finding — the single most important thing the data shows20- The data source and time period covered2122**Optional:**23- The audience (general public, specialist readers, policymakers)24- Any important caveats about the data (methodology limits, missing data, definitional changes over time)25- The tone of the surrounding article (investigative, explanatory, neutral news, opinion)26- Word count target for the narrative text2728## How the Assistant Approaches This291. Identifies the single most significant finding in the data as described — the peak, the gap, the trend reversal, the unexpected comparison — and treats that as the headline finding302. Drafts a chart headline (also called a "active headline" or "tells headline") that states the finding rather than just labeling the chart topic313. Writes an introductory sentence of one to two lines that contextualizes the finding for a reader who may not examine the chart closely324. Produces annotation text or a caption that directs attention to the specific element of the chart that carries the main finding, and notes any caveats the reader needs to interpret the data accurately3334## Output Format35Three distinct text elements, clearly labeled:3637**Chart headline:** One sentence, active voice, states the finding (e.g., "Rental costs in mid-sized cities outpaced wage growth every year from 2018 to 2025"). Maximum 12 words.3839**Introductory sentence:** One to two sentences placed above or beside the chart. Tells the reader what to look for and why it matters. Plain English, no jargon, no hedge language unless the data genuinely requires it.4041**Caption / annotation:** One to three sentences below or beside the chart. Notes the data source, the time period, any methodological caveats, and — if space allows — a secondary observation from the data.4243## Quality Criteria44- [ ] The chart headline states a finding, not just a topic ("Unemployment rises" not "Unemployment rates by region")45- [ ] The introductory sentence does not simply repeat the headline — it adds context46- [ ] Any data caveats mentioned in the input are reflected in the caption47- [ ] No jargon that a general reader would need to look up48- [ ] All three text elements are short enough to be read before the reader decides whether to engage with the chart4950## Example5152### Input53Chart type: Line chart54What it shows: Annual average rent for a two-bedroom apartment in twelve mid-sized cities, compared to median annual wage growth, from 2016 to 202555Key finding: From 2020 onwards, rent increases outpaced wage growth in ten of the twelve cities, with the gap widest in 202356Data source: National Housing Survey, Office of Labor Statistics (both public datasets)57Time period: 2016–202558Audience: General news readers59Caveats: Data covers formal rental market only; short-term rentals excluded60Tone: Neutral news6162### Output63**Chart headline:** Rents raced ahead of wages in most mid-sized cities after 20206465**Introductory sentence:** In ten of twelve cities tracked, the cost of renting a two-bedroom apartment grew faster than the typical worker's annual pay rise every year from 2020 to 2025 — with 2023 marking the widest gap on record.6667**Caption:** Source: National Housing Survey and Office of Labor Statistics, 2016–2025. Figures cover the formal rental market; short-term and informal rentals are not included. Wage growth figures reflect median annual change across all full-time workers in each city.6869## Known Limitations70- This skill works from your description of the chart — it cannot read an image or a data file directly. The quality of the output depends on how precisely you describe the key finding and what the axes represent.71- For charts with multiple competing findings (e.g., some metrics up, some down), you must specify which finding is primary; otherwise the assistant will choose, and it may not be the one your story argument requires.72- Annotation text for highly technical data (epidemiological rates, financial derivatives, scientific measurements) should be reviewed by a subject-matter expert before publication.7374## Related Skills75- [chart-type-advisor](../../../data-journalism/visualization/chart-type-advisor/SKILL.md)76- [dataset-summary-writer](../../../data-journalism/analysis/dataset-summary-brief/SKILL.md)77- [data-corrections-writer](../../../data-journalism/publishing/data-corrections-writer/SKILL.md)