Pluralize and singularize English words
Handles 27 irregular nouns, 16 uncountables, and standard suffix rules. Case preserved for ALL CAPS and Capitalized inputs.
people children mice analyses boxes countries leaves
How to pluralize words
Checks an irregular and uncountable dictionary first, then applies suffix rules (-es, -ies, -ves, -s).
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Type words
One per line or any free-form text. Punctuation is preserved.
Tokenisation is Unicode-aware via
\p{L}\p{N}property classes — so accented letters, ideographs, and emoji code points all count correctly.textUTF-8Unicodecode pointsliveinput · textraw · UTF-8person child mouse
loaded · UTF-8UTF-8 · ready - 02
Pick direction
Pluralize converts singulars to plurals; singularize does the reverse.
Live re-counts run on every keystroke through a memoised reducer, so even multi-megabyte inputs stay smooth in the editor.
modelivememoisedoptionssnappydir · options→ · livepluralize
options applied · livelive - 03
Irregular first
Lookups for 'person → people', 'analysis → analyses' before suffix rules.
Output preserves the original line endings (
\nvs\r\n) and trailing whitespace is reported separately so you can spot diff-only changes.irregline endingswhitespacediff-cleanreproducibledict · counted27 pairs · readyperson → people
counted · livecounted - 04
Copy result
Whole document transformed in place, formatting kept.
Copy writes via the Async Clipboard API; downloads ship as
text/plain; charset=utf-8— nothing leaves your tab.exportclipboardtext/plainblobclient-side✓ · copiedready · done✓ Copied
shipped · ready to shipsuccess
Text-processing fundamentals worth knowing
Tokenise with Unicode classes
Use \p{L}\p{N} with the u flag so accents, ideographs, and emoji count properly.
Normalise line endings
Convert \r\n to \n before diffing or hashing — Windows-vs-Unix endings produce phantom changes.
Mind invisible characters
Zero-width joiners, BOMs, and non-breaking spaces look identical to ASCII space. Strip them before comparison or storage.
Stream don’t slurp
For multi-megabyte text, iterate line-by-line rather than loading everything to memory — keeps the tab responsive.
Choose collation deliberately
Default JS sort is code-point order, not human alphabetical. Use Intl.Collator for locale-aware sorting.
Re-run after normalisation
NFC vs NFD changes byte length but not visible glyphs. String.prototype.normalize() before counts and comparisons.
When to pluralize
Schemas, i18n, copy.
Database tables
Convert model names to table names (User → Users). Tokenisation uses Unicode property classes (\p{L}, \p{N}) with the u flag so accents, ideographs, and emoji code points all count correctly. Surrogate-pair-aware counts mean 🚀 weighs 1, not 2.
Unicode-correctAPI endpoints
REST conventions use plural collections (/users). Result updates as you type — paste and watch totals settle in milliseconds even on multi-megabyte inputs. Heavy work runs through a memoised reducer so the editor never janks.
diff-cleani18n strings
Generate plural variants quickly. Output normalises line endings to LF for clean diffs across platforms. Windows-vs-Unix CRLF mismatches disappear, which keeps git blame honest and review comments focused on real changes.
i18n-friendlyUI labels
Item count labels like '1 item / 2 items'. Code-point counts are stable across NFC/NFD normalisation. Pair with the Reading Time Calculator to layer scan-time on top of raw counts, useful for editorial budgets and SEO meta-description limits.
platform-awareStyle guides
Quick reference for tricky plurals. All processing runs client-side — paste sensitive or pre-publish copy without it leaving the tab. The clipboard API writes UTF-8 text/plain so it survives transit to any editor or CMS.
code-point-accurateDocumentation
Make tutorials consistent (1 file → 2 files). Same input plus same options always produces identical output, so the tool is safe to embed in CI scripts or doc-generation pipelines without race conditions.
losslessFrequently asked questions
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