data-storytelling SKILL.md skillA

data-storytelling from hollandkevint/data-product-operator is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add hollandkevint/data-product-operator/data-storytelling@v0.1.0

Pins v0.1.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
hollandkevint/data-product-operator
Path
skills/data-storytelling/SKILL.md
Versions recorded
2
Latest version
v0.1.0, committed Nov 3, 2026
First version recorded
Feb 20, 2026
Size
3,315 bytes
Repository stars
5
License
MIT

Data presentation and storytelling for data product operators. Narrative structures, chart selection, headline formulas, and anti-patterns. Use when presenting data to stakeholders, building a data presentation, writing an executive summary of findings, telling a data story, or making a case with data. For stakeholder alignment process, see stakeholder-alignment. For metric definitions, see metrics-definition.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

## Headline Formula

Every data finding needs a headline: **[Specific Number] + [Business Impact] + [Actionable Context]**.

"Readmission risk scores now flag 23% more high-risk patients, saving $2.1M annually." Not "We improved our model performance." Not "Results were statistically significant."

The number makes it concrete. The impact makes it relevant. The context makes it actionable.

## Narrative Structures

Pick the structure that matches the situation:

| Structure | When to Use | Shape |
|-----------|------------|-------|
| Problem-Solution | Pitching new work | "Here's the gap, here's what we built" |
| Trend | Status updates | "Here's what changed and why it matters" |
| Comparison | Trade-off decisions | "Here are two options with costs" |

## Narrative Arc for Presentations

**Hook** (the surprise or gap) → **Context** (what the audience needs to know) → **Evidence** (the data, 2-3 charts max) → **Implication** (so what?) → **Recommendation** (now what?)

Start with the finding, not the methodology. Executives care about the answer. They'll ask about the method if they want it.

## Chart Selection

Match the metric type to the right chart:
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add hollandkevint/data-product-operator/data-storytelling@sha256:75332b958894eee1

The line at the top of this page pins the label v0.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_7vy4nwf3bankkqst.svg)](https://markdownregistry.com/a/art_7vy4nwf3bankkqst)

8 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between Feb 20, 2026 and Nov 3, 2026, about one every 256 days.

versioncommittedcommitsizeaudit
v0.1.0 latest2026-11-03 2939ae2 3,315 BA view · diff
v0.1.02026-02-20 b70a111 3,356 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (3315 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

hollandkevint/data-product-operator · 5 stars · license MIT · pushed 2026-11-03 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_7vy4nwf3bankkqst
GET https://markdownregistry.com/api/v1/resolve?ref=hollandkevint/data-product-operator/data-storytelling
GET https://markdownregistry.com/api/v1/blob/75332b958894eee1bf3fd5d0ff9b7be04a74d6601c5922ae04487be5d111698d

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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