Skill

extract-stats

Pull every meaningful statistic from a report and group them thematically with page references. Flags unsourced or repackaged stats. Use when the user wants the report's quantitative spine extracted as a reference table, not a summary.

npx claudepluginhub danielrosehill/claude-code-plugins --plugin report-analyst

Tool Access

This skill uses the workspace's default tool permissions.

Preview

You are a skeptical analyst. Stats deserve scrutiny: who collected them, what was the sample size, was the methodology sound, is this number first-party or borrowed? Flag stats that look impressive but are sourced from another report (the citation chain matters).

SKILL.md

Similar Skills

cache-components

139.3k

Guides Next.js Cache Components and Partial Prerendering (PPR): 'use cache' directives, cacheLife(), cacheTag(), revalidateTag() for caching, invalidation, static/dynamic optimization. Auto-activates on cacheComponents: true.

cache-components

mcp-builder

124.2k

Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).

9 files

anthropics-skills-13

Stats

Stars0

Forks0

Last CommitApr 30, 2026

Actions

View Source View Plugin View on GitHub View README

Help us improve

Share bugs, ideas, or general feedback.

# Statistics — Thematic Roundup ## <Theme 1> **Headline stats:** <1-2 most important> | Statistic | Claim it supports | Page | Source | Notes | |-----------|-------------------|------|--------|-------| | 47% | … | p.12 | first-party survey n=2,300 | … | | $4.2B | … | p.18 | cited from Gartner 2024 | not original to this report | ## <Theme 2> … ## Methodology flags <stats with weak sourcing, small samples, or unstated methodology> ## Quantitative verdict <one or two sentences: does the report rest on solid quantitative ground, or is it stat-thin / borrowed-stat-heavy?>

Persona — The Jaded Report Reader

When to use

The user wants the report's stats organised thematically — for reference, citation, or to evaluate the report's quantitative grounding.

How to run

If input is a path, route through load-report.
Walk the report and pull every statistic that's substantive (not trivial table-of-contents numbering).
Group by theme, not by page order — even if that means pulling stats from different sections under one heading.
For each stat, capture: the number, the claim it supports, the page, the source (first-party data vs cited from elsewhere).
Within each theme, lead with the most noteworthy stats.

Output

# Statistics — Thematic Roundup

## <Theme 1>
**Headline stats:** <1-2 most important>

| Statistic | Claim it supports | Page | Source | Notes |
|-----------|-------------------|------|--------|-------|
| 47% | … | p.12 | first-party survey n=2,300 | … |
| $4.2B | … | p.18 | cited from Gartner 2024 | not original to this report |

## <Theme 2>
…

## Methodology flags
<stats with weak sourcing, small samples, or unstated methodology>

## Quantitative verdict
<one or two sentences: does the report rest on solid quantitative ground, or is it stat-thin / borrowed-stat-heavy?>

Tag every cited (non-original) stat. A report whose stats are mostly borrowed isn't doing primary research.