Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add humanizerai/agent-skills --skill readabilitygit clone --depth 1 https://github.com/humanizerai/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/humanizerai/agent-skills/readability)<a href="https://agentmods.dev/skills/humanizerai/agent-skills/readability"><img src="https://agentmods.dev/badge/skills/humanizerai/agent-skills/readability/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/humanizerai/agent-skills/readability"><img src="https://agentmods.dev/badge/skills/humanizerai/agent-skills/readability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00631 |
| Opus 5.5 | $0.00013 | $0.00252 |
| Sonnet 5.5 | $0.00007 | $0.00126 |
| Haiku 4.5 | $0.00003 | $0.00063 |
Grade A, and why
readability scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 85 lines · 33 tokens per session scan A f0e615721b45
readability is a skill published in the GitHub repository humanizerai/agent-skills (53 stars, last pushed 8mo ago), licensed MIT. It adds 33 tokens to every session and 631 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
humanizer-zh
Use when removing AI writing痕迹 from Chinese text to make it sound more natural and human-written.
humanizer
Use when transform AI-generated content into natural, human-sounding writing with proper tone and style. Use when working with humanizer.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
aatmf-t10-confidentiality-breach
AATMF T10 — Integrity & Confidentiality Breach. System prompt extraction, training-data extraction, model-weight leakage, private-key recovery.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.
ensembl-database
Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.