¿Puedo vibecodear Rephrasy?

NO TANTO · sigue valiendo pagarlo

precio $18.99/mesahorrarías $227.88/añotiempo de build una sentada for the wrapper; the detector-grade part is not a build, it's an ongoing arms racecategoría ✍️ escritura con iareemplazada por 0 personas

You can one-shot a rewriting wrapper that makes text sound less robotic, and for that job the DIY build is genuinely fine. What you cannot one-shot is the actual product: custom fine-tuned models plus a continuous evaluation loop against detectors (GPTZero, Turnitin, Copyleaks, Pangram) that retrain specifically on LLM-rewritten text. A prompted rewrite moves detector scores inconsistently, and detectors drift monthly, so a static prompt that works today quietly stops working. If your bar is 'reads naturally', build it; if your bar is 'passes detectors reliably', the moat is the model and the eval treadmill, not the text box.

el prompt

Build me a local AI-text humanizer workbench. This is the honest consolation build: it makes AI text read naturally, it does NOT promise to beat AI detectors.

Stack: Node 22 + Express, vanilla JS frontend, SQLite via better-sqlite3. No build step.

- One page on localhost:5180: input textarea left, output pane right, a Humanize button, and a strength select (light touch / standard / heavy rewrite).
- Humanize calls an LLM (Anthropic or OpenAI, key in .env) with a fixed system prompt per strength level that: varies sentence length and rhythm, cuts hedging and filler ('delve', 'moreover', 'it's important to note'), swaps uniform paragraph shapes for uneven ones, and keeps meaning, facts, names, and numbers intact. Stream the output.
- A word-level diff view between input and output (the `diff` npm package) so I can see exactly what changed.
- A Re-roll button that re-humanizes the current output with a different seed phrase in the prompt, keeping the last 5 attempts switchable via tabs.
- Every run saved to SQLite: timestamp, strength, input, output. History page with the last 100 runs and copy buttons.
- Cmd+Enter runs humanize.
- .env.example with the key name; README states clearly: output is for readability, no detector-bypass guarantee, and text leaves the machine only for the LLM call.
- Out of scope, deliberately: detector score checking, browser extension, accounts, multi-language tuning, API access.

$ ábrelo en tu agente (prompt listo, tú das enter) o cópialo crudo

por qué la gente sigue pagando

Because 'sounds human to me' and 'passes Turnitin' are different products. Prompt-based rewrites are exactly what modern detectors train on, so DIY results are hit-or-miss and degrade as detectors update. Paying customers are buying a maintained pass rate: someone else fine-tunes models, re-benchmarks against every detector release, and eats the retraining cost when the arms race moves.

qué pierdes

xmodelos afinados entrenados específicamente para superar detectores de IA

xrepruebas continuas a medida que GPTZero/Turnitin/Copyleaks/Pangram se actualizan

xpuntaje de detector integrado para verificar el resultado antes de usarlo

xsoporte para más de 50 idiomas y estilos de escritura personalizados

xextensión para Chrome y API REST

arte previo · úsalo en vez de construir, si prefieres

Nada que valga la pena señalar. Por eso existe el prompt.

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