smithery.ai

readme-writer

Measure and improve the reading level of any prose — docs, READMEs, emails, proposals, specs, plans.

First seen Mar 23, 2026

Installation

$ npx skills add https://smithery.ai

Summary

  • Measure and improve the reading level of any prose — docs, READMEs, emails, proposals, specs, plans.
  • Scores Flesch-Kincaid grade level and top-1000 vocabulary coverage with real scripts instead of estimates.
  • Triggers on 'readability', 'reading level', 'grade level', 'Flesch-Kincaid', 'plain language', 'make this easier to read', 'simplify this writing', 'too dense', 'ESL-friendly', and on 'write readme', 'improve readme', 'readme review', 'documentation writing'.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Skill metadata

Parsed from SKILL.md frontmatter.

LicenseMIT

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,389 B
  • docs SUMMARY.md 135 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Readability and README Writing

Two jobs. The common one: measure and improve reading level in any prose — a doc, an email, a proposal, a spec, a plan. The narrower one: structure a README.

Always Measure — Never Estimate

Syllable counts cannot be eyeballed accurately across a document. Reporting a Flesch-Kincaid score without running the script is guessing. Run it.

cat FILE | ruby scripts/flesch_kincaid.rb

Works on any text, not just markdown — pipe in an email draft, a section of a doc, a paragraph pasted into a heredoc.

Target: grade level 11 or below. Technical terms inflate the score, and that's fine — the goal is to keep the surrounding prose clear so the technical content stays accessible.

Revise, then re-measure. Focus revision on:

  • Shortening sentences (not dumbing down terminology)
  • Replacing complex connectors with simple ones
  • Breaking multi-clause sentences into two

Report the before and after scores.

Vocabulary Coverage

Many readers of technical writing are not native English speakers.

cat FILE | ruby scripts/vocabulary_profiler.rb

Aim to raise the percentage of words in the top 1000 most common English words. Technical terms lower this number — expected. Keep the non-technical words simple.

Do:

  • Use active voice
  • Keep noun phrases short and direct
  • Limit embedded clauses to one level of nesting
  • Use simple "if/then" conditionals
  • Make logical connections explicit with transition words (however, therefore, because)
  • Spread information across multiple sentences when needed

Don't:

  • Stack multiple modifiers before nouns ("the recently revised standardized testing protocol")
  • Rely on mixed or inverted conditionals ("Had she known...")
  • Expect readers to infer relationships between ideas
  • Pack too many new concepts into a single sentence
  • Assume shared knowledge of idioms or cultural references

Flow and Transitions

  • Start with concepts, then details. Give readers the "why" before the "how"
  • Add transitions between major sections so the piece reads as a narrative, not a list of disconnected blocks
  • Create logical progression from high-level to detailed

README Structure

When the document is specifically a README, it flows through these sections:

  1. What and why — what the package does and why it matters (the "what's in it for me")
  2. Install and use — how to get started quickly
  3. Configuration — common options and methods
  4. Contributing — how to contribute, or a pointer to CONTRIBUTING.md. Notes on the build environment and portability
  5. Project layout — unusual top-level directories or files, hints for navigating the source

Formatting

Use GitHub-flavored callout blocks to highlight important information:

[!CAUTION]
[!IMPORTANT]
[!NOTE]
[!TIP]
[!WARNING]

  • Use bold for key concepts on first introduction
  • Use code for commands, filenames, config keys, and values
  • Use concrete, descriptive names for examples ("Invoice Approval" not "Example 1")

Quality Checklist

  • Flesch-Kincaid grade level measured with the script, at or below 11
  • Vocabulary coverage measured; non-technical words kept simple
  • Each section flows naturally into the next
  • Key concepts are bolded on first use
  • Examples use real scenario names, not generic placeholders
  • No corporate buzzwords (comprehensive, robust, seamless, leverage, utilize)
  • Terminology is consistent throughout (same word for same concept)
  • Acronyms and specialized terms are defined on first use
  • Active voice is used wherever possible

Bibliography