dataset-summary-brief

dataset-summary-brief is a skill for Claude Code from ur-grue/autopunk-media-skills. It costs 45 tokens per session (1,603 once invoked), scanned A, original, MIT.

A skill that reviews a dataset and creates a briefing about what it contains, what it covers, its limits, and which reporting angles it may support.

In plain words
What is it for?
Use it to assess a dataset's source, fields, time period, geographic coverage, quality issues, and possible news value.
Why use it?
It helps decide whether a dataset is suitable for further journalism before spending time on reporting.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the autopunk-media-skills plugin — 187 skills shipped together

Good fit Use it to assess a dataset's source, fields, time period, geographic coverage, quality issues, and possible news value.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ur-grue/autopunk-media-skills/dataset-summary-brief
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ur-grue/autopunk-media-skills --skill dataset-summary-brief
Clone the repo
git clone --depth 1 https://github.com/ur-grue/autopunk-media-skills

Made for: Claude Code.

Or install autopunk-media-skills, the plugin that ships this one along with the rest of its 187 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dataset-summary-brief

README.md
[![agentmods](https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/dataset-summary-brief/github.svg)](https://agentmods.dev/skills/ur-grue/autopunk-media-skills/dataset-summary-brief)
Your own site
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/dataset-summary-brief"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/dataset-summary-brief/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dataset-summary-brief

Your own site · 80×15
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/dataset-summary-brief"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/dataset-summary-brief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,603 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.01603
Opus 5 $0.00023 $0.00801
Sonnet 5 $0.00009 $0.00321
Haiku 4.5 $0.00005 $0.00160

Measured 12d ago against content hash 3b048318d522, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

dataset-summary-brief scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/data-journalism/analysis/dataset-summary-brief/SKILL.md · 105 lines

How it starts

The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dataset Summary Brief

What This Skill Does

Produces a structured summary of what a dataset contains, what it covers, what its limitations are, and what story angles it could plausibly support — written as a briefing document for a journalist or editor.

When To Use This Skill

  • You have received a new dataset and need to assess its news potential quickly before committing reporting time
  • You need to brief an editor, producer, or commissioning colleague on what a dataset does and doesn't contain
  • You are handing off a dataset to another journalist and need to document what you found
  • You want to identify data gaps before deciding whether additional FOI requests or data collection are needed

What You Need To Provide

Required: A description of the dataset — source, title or file name, number of rows and columns, time period covered, geographic scope, and a list of column names with brief descriptions of what each contains. Optional: A small representative data sample; any known issues with the data (missing values, format inconsistencies); the context in which the data was obtained (FOI response, published report, leaked document).

How the Assistant Approaches This

  1. Reviews the structure description and identifies the key variables, time dimensions, and geographic granularity of the dataset.
  2. Assesses the dataset's completeness and potential limitations — missing periods, incomplete geographies, definitional ambiguities, and likely data quality issues.
  3. Writes a structured brief covering: what the dataset is and where it came from, what it can and cannot show, and three to five story angles it could support.

Output Format

A one-page briefing document (approximately 400–600 words) structured under four headings: What This Dataset Is, What It Covers, Limitations and Caveats, and Potential Story Angles. Tone: direct and editorial — written for a journalist colleague, not a data scientist. No statistics formulae. Plain language throughout.

Read the full file on GitHub · 105 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 105 lines · 45 tokens per session scan A 3b048318d522

Subscribe to this mod's changes

dataset-summary-brief is a skill published in the GitHub repository ur-grue/autopunk-media-skills (32 stars, last pushed 12d ago), licensed MIT. It adds 45 tokens to every session and 1,603 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.