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example-skill skill

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This skill analyzes text to compute word counts, reading time, complexity metrics, and readability scores, helping you evaluate documents quickly.

npx playbooks add skill leegonzales/aiskills --skill example-skill

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SKILL.md

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---
name: text-statistics
description: Analyze text for word count, reading time, complexity metrics, and readability scores. Use when user asks to analyze document length, calculate reading time, or assess text complexity.
---

# Text Statistics

Quick analysis of text metrics including word count, reading time, complexity, and readability.

## When to Use

Invoke when user:
- Asks "how long is this text?"
- Wants reading time estimates
- Needs complexity or readability scores
- Says "analyze this document" or "how many words?"

## Core Capabilities

### 1. Basic Metrics

**Word Count**
- Total words
- Unique words
- Average word length

**Character Count**
- With and without spaces
- Alphanumeric vs punctuation

**Reading Time**
- Assuming 200-250 words/minute
- Adjusted for complexity

### 2. Complexity Analysis

**Sentence Structure**
- Average sentence length
- Sentence length variance
- Simple vs complex sentences

**Vocabulary**
- Unique word ratio
- Long word percentage (7+ chars)
- Syllable count estimates

### 3. Readability Scores

**Flesch Reading Ease**
- 0-100 scale
- Higher = easier to read

**Grade Level Estimate**
- US grade level equivalent
- Based on sentence/word complexity

## Output Format

```
TEXT STATISTICS REPORT
=====================

Basic Metrics:
- Word Count: X (Y unique)
- Character Count: X (Y without spaces)
- Reading Time: X-Y minutes

Complexity:
- Avg Sentence Length: X words
- Long Words (7+ chars): X%
- Vocabulary Richness: X%

Readability:
- Flesch Score: X/100 (Level)
- Grade Level: X

Interpretation:
[Brief assessment of text complexity and audience appropriateness]
```

## Examples

See `references/examples.md` for analyzed samples.

## Integration

Standalone skill. Useful before:
- Prose Polish (get baseline metrics)
- Content generation (target metrics)

Overview

This skill analyzes text to provide word and character counts, reading time estimates, complexity metrics, and readability scores. It gives a concise report that helps you judge length, audience level, and where to focus editing. Use it to quickly quantify and interpret a document’s readability and structure.

How this skill works

The skill inspects the input text to compute basic metrics (total and unique words, characters, average word length) and estimates reading time using standard words-per-minute ranges with adjustments for complexity. It parses sentences to measure average sentence length and variance, flags long words and estimates syllable counts, then calculates Flesch Reading Ease and a US grade-level estimate. Results are returned in a compact, human-readable report with interpretation guidance.

When to use it

You ask “how long is this text?” or need a word/character count
Estimate reading time for articles, speeches, or transcripts
Assess whether text is appropriate for a target audience or grade level
Compare drafts by complexity or readability before publishing
Prepare content to meet accessibility or editorial standards

Best practices

Provide the full text or a representative sample for accurate metrics
Specify target reading speed or audience if you need custom estimates
Use the grade-level and Flesch score together to judge accessibility
Combine with editing workflows: metrics guide where to shorten sentences or simplify vocabulary
Run comparisons between drafts to measure improvement quantitatively

Example use cases

Calculate reading time and word count for a blog post to set publishing expectations
Evaluate textbook excerpts to confirm they match a target grade level
Assess marketing copy to ensure it reads as plain language for broad audiences
Measure complexity changes across revised drafts to track simplification efforts
Generate baseline metrics before automated rewriting or human editing

FAQ

What reading speed does the tool assume?

By default it uses 200–250 words per minute and provides a range; you can supply a different WPM for custom estimates.

How accurate are syllable and complexity estimates?

Estimates use common heuristics (character patterns and vowel clusters). They are good for comparative and approximate analysis but not perfect for every language or exceptional vocabulary.