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data-narrative-builder

data-narrative-builder

github.com/nimrodfisherData & databases504230 installsUpdated 5w ago
Repository

About data-narrative-builder

A skill for turning data analysis into decision-oriented presentations, aimed at analysts who need to communicate findings and prompt action. It combines narrative frameworks, emotional pacing, data-writing guidance, and a fill-in template.

Key features

  1. 01Distill a central message
  2. 02Choose a narrative structure
  3. 03Plan the emotional arc
  4. 04Weave data into sections
  5. 05Sequence charts and visuals
  6. 06Draft the hook and call to action

Use cases

  1. 01Turn data-heavy slides into a story
  2. 02Present concise findings to senior audiences
  3. 03Restructure recurring reports around a narrative

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/nimrodfisher/data-analytics-skills --skill data-narrative-builder

After installing, type/data-narrative-builderin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

assets/
narrative_template.md
references/
data_writing_guide.md
narrative_frameworks.md

Details

From the project README

Data Narrative Builder

When to use

  • A presentation exists but feels like a data dump rather than a story
  • The analysis has a clear finding but the team doesn't know how to make it compelling
  • The audience is senior and will not read more than 5 slides
  • A decision needs to be made and the data needs to make a clear, emotion-aware argument
  • A recurring report needs to be restructured around a narrative rather than a metric list

Process

  1. Identify the central message — write the single most important thing the audience should know and do after seeing this. Everything else is supporting material. If there's more than one message, there are multiple presentations.
  2. Choose a narrative framework — select the structure that fits the context. Situation–Complication–Resolution works for most problem/solution stories. Before–After–Bridge is strong for demonstrating impact. See references/narrative_frameworks.md for all patterns with examples.
  3. Assign an emotional arc — map each section to an intended emotional state: establish comfort (Situation), introduce tension (Complication), offer confidence (Resolution). Tone and data emphasis should match the intended emotion at each stage.
  4. Draft each section with data woven in — apply the pyramid principle: lead with the conclusion, then support it with evidence. Numbers must serve the narrative, not interrupt it. Round large numbers for recall; humanise by expressing impact in terms the audience cares about.
  5. Plan the visual sequence — assign one key chart or visual to each narrative beat. The visual should reinforce the spoken or written message, not repeat it. See references/data_writing_guide.md for annotation and emphasis techniques.
  6. Write the opening hook and closing call to action — the hook must earn attention in under 10 seconds (a surprising stat, a question, or a contrast). The CTA must name a specific decision, person, and deadline. Complete assets/narrative_template.md.

Inputs the skill needs

  • The central finding or insight to be communicated
  • The audience (role, knowledge level, what they care about most)
  • The desired action or decision at the end of the presentation
  • All supporting data and charts already prepared
  • Format and time constraints (slides, report, 5-minute presentation, 30-page doc)

Output

  • references/narrative_frameworks.md — SCR, BAB, hero journey, and sparklines patterns with data storytelling examples
  • references/data_writing_guide.md — pyramid principle, number formatting, annotation, plain-language techniques
  • assets/narrative_template.md — fill-in-the-blank narrative structure: hook, situation, complication, resolution, call to action

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