Pros of unified

• More versatile and extensible, supporting multiple syntax trees (ASTs) for various content types
• Larger ecosystem with plugins for parsing, transforming, and serializing different formats
• Better suited for complex document processing pipelines

Cons of unified

• Steeper learning curve due to its more comprehensive architecture
• May be overkill for simple text processing tasks
• Requires more setup and configuration for basic use cases

Code comparison

unified:

import { unified } from 'unified'
import remarkParse from 'remark-parse'
import remarkRehype from 'remark-rehype'
import rehypeStringify from 'rehype-stringify'

unified()
  .use(remarkParse)
  .use(remarkRehype)
  .use(rehypeStringify)
  .process('# Hello, world!')
  .then((file) => console.log(String(file)))

retext:

import { retext } from 'retext'
import retextPos from 'retext-pos'
import retextKeywords from 'retext-keywords'

retext()
  .use(retextPos)
  .use(retextKeywords)
  .process('Hello, world!')
  .then((file) => console.log(String(file)))

Summary

unified is a more powerful and flexible tool for processing various types of content, while retext focuses specifically on natural language processing. unified offers a wider range of capabilities but may require more setup, whereas retext provides a simpler approach for text-specific tasks. Choose unified for complex document processing needs and retext for straightforward natural language analysis.

Pros of remark

• Broader ecosystem with more plugins and integrations
• Better suited for Markdown processing and transformation
• More active development and larger community support

Cons of remark

• Steeper learning curve due to more complex architecture
• Potentially slower processing for simple text operations
• May be overkill for projects that don't require Markdown handling

Code Comparison

remark:

import { remark } from 'remark';
import remarkHtml from 'remark-html';

const markdown = '# Hello, world!';
remark()
  .use(remarkHtml)
  .process(markdown)
  .then((file) => console.log(String(file)));

retext:

import { retext } from 'retext';
import retextPos from 'retext-pos';

const text = 'The quick brown fox jumps over the lazy dog.';
retext()
  .use(retextPos)
  .process(text)
  .then((file) => console.log(String(file)));

Both remark and retext are part of the unified ecosystem, but they serve different purposes. remark is primarily focused on Markdown processing, while retext is designed for natural language processing. remark offers a more extensive plugin ecosystem and is better suited for projects involving Markdown transformation. However, retext excels in text analysis and manipulation tasks, making it a more appropriate choice for natural language processing applications.

Pros of textlint

• More extensive rule ecosystem with a wide range of community-contributed plugins
• Supports multiple markup languages (Markdown, AsciiDoc, Re:VIEW)
• Provides a command-line interface for easy integration into workflows

Cons of textlint

• Steeper learning curve due to more complex configuration options
• Slower performance on large documents compared to retext
• Less focus on natural language processing tasks

Code Comparison

textlint configuration:

{
  "rules": {
    "no-todo": true,
    "max-comma": { "max": 3 },
    "spellcheck-tech-word": true
  }
}

retext usage:

import {retext} from 'retext'
import retextSpell from 'retext-spell'
import dictionary from 'dictionary-en-us'

retext()
  .use(retextSpell, dictionary)
  .process('Some text to analyze')

Both textlint and retext are powerful text analysis tools, but they cater to slightly different use cases. textlint offers more flexibility for various markup languages and has a larger ecosystem of rules, making it suitable for complex documentation projects. retext, on the other hand, focuses more on natural language processing tasks and provides a simpler API, making it easier to integrate into JavaScript projects for specific text analysis needs.

Pros of Vale

• Written in Go, offering better performance and easier deployment
• Extensive rule set and customizable style guides out-of-the-box
• Integrates well with various text editors and CI/CD pipelines

Cons of Vale

• Less flexible for programmatic text transformations
• Steeper learning curve for creating custom rules
• Limited to linting and doesn't provide text manipulation capabilities

Code Comparison

Vale configuration (.vale.ini):

StylesPath = styles
MinAlertLevel = suggestion

[*.md]
BasedOnStyles = Vale, proselint

Retext usage:

import {retext} from 'retext'
import retextSpell from 'retext-spell'
import dictionary from 'dictionary-en-us'

retext()
  .use(retextSpell, dictionary)
  .process('Some text to analyze')

Vale focuses on configuration-based linting, while Retext provides a programmable pipeline for text analysis and transformation. Vale excels in ready-to-use style checking, whereas Retext offers more flexibility for custom text processing tasks.

Pros of write-good

• Lightweight and easy to use with minimal setup
• Focuses specifically on writing style improvements
• Provides clear, actionable suggestions for better writing

Cons of write-good

• Less extensible compared to retext's plugin system
• Limited to English language analysis
• Fewer customization options for specific use cases

Code Comparison

write-good:

var writeGood = require('write-good');
var suggestions = writeGood('So the cat was stolen.');
console.log(suggestions);

retext:

var retext = require('retext');
var english = require('retext-english');
var stringify = require('retext-stringify');
var passive = require('retext-passive');

retext()
  .use(english)
  .use(passive)
  .use(stringify)
  .process('So the cat was stolen.')
  .then((file) => console.log(String(file)));

write-good provides a simpler API for quick writing improvements, while retext offers a more modular and extensible approach for text processing and analysis. write-good is ideal for straightforward writing enhancement, whereas retext is better suited for complex natural language processing tasks and customizable text transformations.