word-stats
npx machina-cli add skill humanizerai/agent-skills/word-stats --openclawWord Statistics
Provide quick, accurate statistics about the provided text.
Input
The user provides text in $ARGUMENTS.
Important: If text is provided, immediately output stats. Don't ask clarifying questions - they want the numbers.
Output Format
## Word Statistics
### Counts
| Metric | Value |
|--------|-------|
| Words | [X] |
| Characters (with spaces) | [X] |
| Characters (no spaces) | [X] |
| Sentences | [X] |
| Paragraphs | [X] |
### Time
| Metric | Value |
|--------|-------|
| Reading time | [X] min |
| Speaking time | [X] min |
### Words
| Metric | Value |
|--------|-------|
| Unique words | [X] ([Y]%) |
| Avg word length | [X] chars |
| Longest word | [word] ([X] chars) |
### Sentences
| Metric | Value |
|--------|-------|
| Avg length | [X] words |
| Longest | [X] words |
| Shortest | [X] words |
Calculations
- Reading time: words ÷ 238 (average adult reading speed)
- Speaking time: words ÷ 150 (average speaking pace)
- Unique words: distinct words ÷ total words × 100
Keep It Simple
- Tables for metrics
- No unnecessary prose
- No recommendations unless asked
- Just the numbers
Source
git clone https://github.com/humanizerai/agent-skills/blob/main/skills/word-stats/SKILL.mdView on GitHub Overview
Word stats provides quick statistics about the provided text, including words, characters with and without spaces, sentences, and paragraphs, plus reading and speaking times. It also surfaces metrics like unique word percentage, average word length, and the longest word in simple tables. No clarifying questions are asked; results are delivered as numbers only.
How This Skill Works
The skill consumes input text through ARGUMENTS, counts core metrics (words, characters with spaces, characters without spaces, sentences, paragraphs), and computes derived values (reading time and speaking time). It also analyzes unique words, average word length, and the longest word, presenting all results in structured tables.
When to Use It
- Before publishing a blog post or article to estimate length and readability
- Comparing two variants of marketing copy for wordiness and clarity
- Auditing product descriptions to ensure concise length
- Assessing long-form content to plan editing and pacing
- Preparing a metrics sheet for a content brief or editorial guidelines
Quick Start
- Step 1: Provide the text to analyze in the ARGUMENTS field
- Step 2: Run the word-stats skill to compute metrics
- Step 3: Review the results in the metrics tables
Best Practices
- Always provide the text to analyze in ARGUMENTS to trigger immediate stats
- Expect results in metrics tables with numeric values only, no extra prose
- Rely on the built in calculations for reading time (words ÷ 238) and speaking time (words ÷ 150)
- Note that Unique words percentage is distinct words ÷ total words × 100
- Use the results to inform editing, budgeting, or content strategy without additional prompts
Example Use Cases
- Audit a product description to verify it stays under a target word count while retaining key features
- Compare two ad copy variants for readability and wordiness
- Estimate reading time for a long form guide before publishing
- Evaluate a news article for the longest and average word lengths to inform style choices
- Prepare a metrics sheet for a content brief to align with SEO and length targets
