Readability
- 422 installs
- 38 repo stars
- Updated February 5, 2026
- humanizerai/agent-skills
readability is a developer-facing readability analysis skill that computes metrics like Flesch-Kincaid and SMOG for developers who need objective scores and recommendations for technical text.
About
readability is a text analysis skill that calculates standardized readability metrics for developer-facing documentation, release notes, and technical copy. The skill computes scores such as Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, and SMOG, then returns objective interpretations and recommendations based on the measured results. Developers reach for readability when API docs feel too dense, onboarding guides need to be more scannable, or a team wants measurable targets for documentation quality instead of subjective feedback. readability is useful as a lightweight review step before publishing docs to reduce comprehension friction for engineers and end users.
- Shorter sentences and simpler vocabulary
- Scannable headings and bullet structure
- Jargon reduction without losing accuracy
- Tone consistency checks
- Before-and-after readability passes
Readability by the numbers
- 422 all-time installs (skills.sh)
- +17 installs in the week ending Aug 2, 2026 (Skillselion tracking)
- Ranked #802 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Data as of Aug 3, 2026 (Skillselion catalog sync)
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| Installs | 422 |
|---|---|
| repo stars | ★ 38 |
| Last updated | February 5, 2026 |
| Repository | humanizerai/agent-skills ↗ |
How do I measure readability of documentation text?
Rewrite marketing copy, docs, and emails to improve clarity, scannability, and reading level while preserving meaning and brand voice.
Who is it for?
Developers who want objective readability scores for documentation and technical copy.
Skip if: Developers who need grammar-only proofreading without quantitative scoring.
When should I use this skill?
Trigger readability when a developer asks to measure or improve the readability level of docs, emails, or release notes using standard metrics.
What you get
Readability metric scores, interpretations, and improvement recommendations.
- Readability scores
- Recommendations
Files
Analyze Readability
Calculate and display readability metrics for the provided text.
Input
The user provides text in $ARGUMENTS. If no text provided, ask for it.
Metrics to Calculate
Core Scores
| Metric | Formula | Interpretation |
|---|---|---|
| Flesch Reading Ease | 206.835 - 1.015(words/sentences) - 84.6(syllables/words) | 0-100, higher = easier |
| Flesch-Kincaid Grade | 0.39(words/sentences) + 11.8(syllables/words) - 15.59 | US grade level |
| Gunning Fog Index | 0.4[(words/sentences) + 100(complex words/words)] | Years of education |
| SMOG Index | 1.043 × √(complex words × 30/sentences) + 3.1291 | Grade level |
Complex words = 3+ syllables
Text Statistics
- Word count
- Sentence count
- Average sentence length (words)
- Average word length (characters)
- Complex words count and %
- Passive voice sentences (estimate)
Output Format
## Readability Analysis
### Scores
| Metric | Score | Meaning |
|--------|-------|---------|
| Flesch Reading Ease | [X] | [interpretation] |
| Flesch-Kincaid Grade | [X] | [grade level] |
| Gunning Fog | [X] | [years education] |
| SMOG | [X] | [grade level] |
### Statistics
- Words: [X]
- Sentences: [X]
- Avg sentence length: [X] words
- Complex words: [X] ([Y]%)
### Target Audience
[Who can easily read this based on scores]
### Recommendations
1. [Specific suggestion]
2. [Specific suggestion]
3. [Specific suggestion]Interpretation Guide
| Flesch Score | Grade | Audience |
|---|---|---|
| 90-100 | 5th | Very easy |
| 80-89 | 6th | Easy |
| 70-79 | 7th | Fairly easy |
| 60-69 | 8-9th | Standard |
| 50-59 | 10-12th | Fairly difficult |
| 30-49 | College | Difficult |
| 0-29 | Graduate | Very difficult |
Recommendations
Based on scores, suggest:
- Sentences to shorten (if avg > 20 words)
- Complex words to simplify
- Passive voice to convert to active
- Specific examples of what to fix
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Pick this when you want quantitative readability scores; pick a copyeditor skill when you want style rewrites without metrics.
FAQ
Which metrics does readability calculate?
readability calculates multiple standardized metrics including Flesch Reading Ease, Flesch-Kincaid Grade, Gunning Fog, and SMOG as listed in its specification. readability returns objective scores along with interpretation guidance and improvement recommendations based on those s
When should readability run in a docs workflow?
readability should run before publishing or merging documentation changes, when you want to quantify difficulty and reduce comprehension friction. readability is especially helpful for onboarding docs, API guides, and release notes where a measurable grade level can guide edits.