Writing and content decision

Lebonsynonyme

A single developer can reproduce the core synonym lookup, voting and suggestion features in ~30 hours and run it for a small audience; the site’s value is mostly content and traffic rather than hard-to-recreate moats so self‑hosting is practical.

Visit website

Built by Nicolas Le Roux 🇪🇺, who ships 5 products in this index

You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$50one-off30 h to build

$15/mo3 h/mo upkeep

No published price to break even against.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • User enters a word → lookup synonyms → display list with votes → allow vote or submit suggestion → store updates and show updated ranking.

What it still won’t have

  • Public site traffic, SEO and domain age that bring organic users
  • Any existing user-contributed synonym corpus and history
  • Polish and branding of the hosted site

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

Lebonsynonyme does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal synonym lookup web app using Node.js + Express, Postgres, and React. Core features: 1) searchable synonym endpoint that returns an alphabetically ordered list; 2) frontend with search box, alphabet index, synonyms list, vote buttons, and suggestion form; 3) backend endpoints to record votes and submit suggestions; 4) simple admin endpoint to review/approve suggestions; 5) persist synonyms, suggestions and vote counts in Postgres; 6) input validation, rate limiting, error handling, and unit/integration tests. Out of scope: training NLP models or external paid APIs for synonym generation. Provide Dockerfiles and a deployment script for a small VPS, and health checks.
How we checked3 sources · 3/3 runs agreed · evidence score 85

How the score was reached

  • Build verdict base78
  • 3 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score85

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded