A comprehensive text analysis tool providing word counts, readability scores, and keyword density for content optimization.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install word-counter
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install word-counter using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Word Counter?
The Word Counter skill is a robust utility designed for developers and content creators using Openclaw Skills to perform deep linguistic analysis. Beyond simple counting, this tool evaluates document structure, estimates reading and speaking durations, and calculates complexity using the Flesch-Kincaid grade level formula.
By integrating this skill, users can ensure their text meets specific platform constraints—from social media character limits to long-form blog requirements—while maintaining an optimal reading experience. It serves as a vital component for anyone looking to refine their writing with data-driven insights.
Word Counter Use Cases
- Validating word and character counts for social media posts, essays, and blog content.
- Estimating the duration of scripts for presentations or video narrations using speaking time metrics.
- Improving SEO performance by analyzing keyword density and frequency within articles.
- Ensuring content accessibility by monitoring readability scores and grade level requirements.
- Auditing document structure by tracking sentence and paragraph distribution.
How Word Counter Works
- The user provides a text string or a file path to the word_counter.py script within the Openclaw Skills environment.
- The system processes the input, normalizing whitespace and handling special characters to ensure accurate word and character counts.
- The engine applies the Flesch-Kincaid algorithm to determine the reading level and document complexity.
- Time-based estimations are calculated based on standard averages (200 wpm for reading, 130 wpm for speaking).
- A structured analysis report is generated, including a ranked list of keywords for SEO optimization.
Word Counter Setup
To integrate this skill into your workflow, ensure the script is located in your scripts directory and execute it via the CLI. This is a core utility for many Openclaw Skills implementations.
# Run analysis on a direct text string
python scripts/word_counter.py "Your analysis text goes here"
# Run analysis on a local text file
python scripts/word_counter.py --file path/to/document.txt
Word Counter Data Schema & Taxonomy
The skill provides a structured output of text metrics. Below is the organization of the data generated during analysis:
| Metric | Purpose | Data Type |
|---|---|---|
| Word/Char Count | Basic length verification for platform limits | Integer |
| Reading/Speaking Time | Estimates duration for consumers or presenters | Minutes/Seconds |
| Readability Level | Flesch-Kincaid grade level assessment | Float/String |
| Keyword Density | Frequency-based ranking for SEO analysis | List/Table |
| Structural Count | Sentence and paragraph distribution tracking | Integer |
Word Counter Advanced Features
- Multi-source analysis allowing for both raw string input and file-based processing.
- SEO-focused keyword density ranking to identify primary and secondary content themes.
- Specialized readability scoring using the Flesch-Kincaid grade level formula for professional editing.
- Customizable time-based metrics for different delivery speeds (reading vs. speaking).
- Platform-aware constraints to help match requirements for X, LinkedIn, and Meta descriptions.
SKILL.md
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