zhangxiangliang/easyen/easy-english

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Checking that the SKILL.md file is still in the repository.

Check how easy an English text is to read, and make it simpler. Measures vocabulary level and sentence length with the easyen CLI, then points at the exact hard words to reword and long sentences to break up. Use it when writing or reviewing English that should stay plain — docs, a README, error messages, release notes — or to hold your own writing at a chosen reading level.

Install

npx vskill@latest install zhangxiangliang/easyen/easy-english

SKILL.md

easyen

See how easy a piece of English is to read, by running npx easyen. It gives you two simple signals — you decide what to change:

  1. Words — how many of the words are in a chosen word list, and which words

are too hard.

  1. Sentences — the average sentence length, and which sentences are long.

easyen only reports. It does not change your text. You decide which hard words to make simpler and which long sentences to break up.

When to use

  • You wrote some English and want it to stay simple for the reader.
  • You want to find the hard words or long sentences in a text.
  • You want to keep your writing at a level (everyday, academic, or technical).

How to run

No install needed — npx easyen gets the package on first run. It reads text from stdin and prints JSON. Pipe the text in, using whatever your shell offers (this follows the Unix convention, and works on macOS, Linux, and Windows PowerShell / cmd). everyday is the default word list.

bash
cat your-doc.md | npx easyen # macOS / Linux
Get-Content your-doc.md | npx easyen # Windows PowerShell

If piping is hard on your system, read a file directly instead:

bash
npx easyen --file your-doc.md --dict everyday,tech

For Markdown (a README, docs, a skill file), add `--markdown`. Without it, code blocks, URLs and HTML count as words, and the result is mostly noise — on this project's own README that alone moved the ratio from 0.94 to 0.83.

bash
npx easyen --file README.md --dict everyday,tech --markdown
Choose a word list by reader

everyday is the base. The others are add-ons — combine them onto everyday, like everyday,academic; each one only adds its own extra words.

  • everyday — the base, about 2800 common words. Use it alone for the simplest level.
  • academic — academic words. --dict everyday,academic
  • tech — software words (api, deploy, schema ...). --dict everyday,tech
  • frameworks — tool and language names (vue, vite, webpack, docker ...).

--dict everyday,tech,frameworks for a frontend or server text.

Use only what the reader needs — a smaller list marks more words to change. You can also add your own word file (one word per line), e.g. your team's product names:

bash
cat your-doc.md | npx easyen --dict everyday,tech,./our-product-names.txt

Reading the result

The JSON has:

  • ratio — 0 to 1, how much of the text is in the word list (higher = easier).
  • hardWords — words not in the list, sorted A–Z. These are the ones to change.
  • hardWordCounts — the same words with how many times each one appears, most

first. Fix the common ones first.

  • sentences.wordsPerSentence — the average sentence length (lower reads easier).
  • sentences.longSentences — sentences over 30 words. These are the ones to

break up.

What to do with it

These are defaults, not rules. Adapt them to your project, your reader, and your taste — projects differ, and readers know different words. The signals show you what to look at; you choose what to change.

Hard words. A hard word may have a simpler form (verify → check) — change it. Or it may be a needed term (an api name), or a word the reader already knows (a reader who learned English for an exam may find implement easier than "carry out") — then keep it. You decide, based on the reader.

Long sentences. Split them: one idea per sentence, about 15–20 words, subject then verb then object. Avoid chaining ideas with "which" / "that", and avoid stacking nouns ("data migration rollback procedure" → "a plan to undo the data change").

A few habits that help, when they fit:

  • Keep a technical term, but explain it the first time ("idempotent — safe to

run more than once with the same result").

  • Use the same word for the same thing every time (not ticket → task → work item).
  • Drop idioms and slang ("a piece of cake" → "easy").
  • Prefer short paragraphs, lists, and one example after each point.

Then run easyen again to check the signals improved.

Notes

  • Use --markdown on any Markdown file. For other formats, strip the code and

links yourself first, so they do not count as hard words.

  • Keep the word list small — that is the point: a small list marks more words to

make simpler. Do not reach for a bigger list just to raise the score.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
2
7-day trend score
5

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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