Can Grammarly be vibe coded?
Grammar, clarity, tone, and AI writing assistant across apps
You can build grammar checks and rewrites, but Grammarly's moat is cross-app extensions, inline UX, enterprise controls, writing telemetry, and long-running language quality.
Jump to the build brief ↓Checked Jul 2026
What you pay today, before any DIY hosting
medium editorial confidence
Buildability by layer
Screens, forms, and focused interactions
The repeatable job the product performs
Availability and legality of required data
Uptime, queues, support, and maintenance
Security, compliance, and user confidence
The achievable core
- Run text through LanguageTool plus an LLM rewrite/tone checker, expose a browser extension or local editor.
- Wrap a model API in a focused drafting, revision, and export workflow.
- A responsive interface with real empty, loading, success, and error states.
The parts a prompt cannot buy
- inline suggestions everywhere
- document/email integrations
- tone/brand controls
- enterprise admin
- Connectors, OAuth flows, and vendor API changes require constant upkeep.
- Model quality and inference operations are part of the product.
Why people still pay
They pay because suggestions appear inside the apps where writing actually happens.
Connectors, OAuth flows, and vendor API changes require constant upkeep.
Model quality and inference operations are part of the product.
The last 20 percent is sync, migration fidelity, speed, and edge cases.
The brief
Context, requirements, acceptance criteria, non-goals, and the full production standard — as Markdown, ready for any coding agent.
Build brief — a focused alternative to Grammarly
Context
**Grammarly** — Grammar, clarity, tone, and AI writing assistant across apps. It currently costs $30/mo.
You can build grammar checks and rewrites, but Grammarly's moat is cross-app extensions, inline UX, enterprise controls, writing telemetry, and long-running language quality.
This brief describes a focused, single-operator replacement for the part of Grammarly that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.
What you are building
Run text through LanguageTool plus an LLM rewrite/tone checker, expose a browser extension or local editor.
Wrap a model API in a focused drafting, revision, and export workflow.
A responsive interface with real empty, loading, success, and error states.
Requirements
Functional
Browser extension.
Optional desktop accessibility layer.
User dictionary.
Data and integrations
Grammar engine/API.
LLM API.
Each of these needs a real account, credential, or quota. Set them up before writing feature code.
Non-functional
Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
Security: server-side secrets, validated input, and no credentials in the client bundle.
Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
Portability: the operator can export their data and leave without losing it.
Implementation brief
Build me a personal writing checker to replace Grammarly. Requirements:
Grammar engine: LanguageTool running locally via its official Docker image;
grammar checks never leave my machine.
A local web page (Node + Express, binds to localhost): paste text, see
LanguageTool issues underlined with hover explanations, click a suggestion
to apply it.
An LLM rewrite pane (key in .env) with three buttons: tighten, friendlier,
formal. Show a diff against my original before I accept anything.
A personal dictionary file (dictionary.txt) of names and jargon to never
flag, passed to LanguageTool on every check.
CLI mode: `check <file.md>` prints issues with line numbers, exits nonzero
if any, so it can run as a git pre-commit hook on docs.
Everything local except the optional LLM call; no accounts, no telemetry.
Out of scope: a browser extension and inline suggestions inside Gmail,
Docs, or Slack. This is a destination I paste into, that is the honest
trade against Grammarly.
README: Docker setup for LanguageTool, the roughly 1 GB of RAM it wants,
and where the LLM key goes.
Delivery standard
Inspect the repository first, then write a short implementation plan before writing code.
Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
Add structured logs around every external call and return actionable errors without leaking sensitive details.
Write unit tests for the core logic and one automated test of the main user journey.
Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.
Acceptance criteria
A clean install starts the app using only the README and .env.example.
The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
Tests, type checking, linting, and a production build all pass with no ignored failures.
No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.
Non-goals
Do not build these, and do not claim to have replaced them:
Inline suggestions everywhere.
Document/email integrations.
Tone/brand controls.
Enterprise admin.
Connectors, OAuth flows, and vendor API changes require constant upkeep.
Model quality and inference operations are part of the product.
What you still own after launch
Secure credentials, rotate secrets, and handle provider rate limits.
Run migrations, backups, restores, and dependency updates.
Test the critical journey after every model, API, or hosting change.
Monitor failures and fix the edge cases a first prompt will miss.
Maintain every third-party integration as APIs and OAuth rules change.
Risk
**Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost.
Editorial confidence in this assessment: medium. No independent one-shot implementation is linked yet.
Prior art
Working open-source software you can read, fork, or borrow from before starting:
[LanguageTool](https://github.com/languagetool-org/languagetool) — Open-source grammar and style checker and the primary Grammarly-like prior art
Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/grammarly
You still own the product
- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.
- Maintain every third-party integration as APIs and OAuth rules change.
Open-source prior art
Before you start
Can Grammarly be vibe coded?
Partly, if you narrow it. You can build grammar checks and rewrites, but Grammarly's moat is cross-app extensions, inline UX, enterprise controls, writing telemetry, and long-running language quality.
What can an AI coding agent reproduce from Grammarly?
Run text through LanguageTool plus an LLM rewrite/tone checker, expose a browser extension or local editor. Wrap a model API in a focused drafting, revision, and export workflow. A responsive interface with real empty, loading, success, and error states.
What will a DIY Grammarly replacement still be missing?
inline suggestions everywhere; document/email integrations; tone/brand controls; enterprise admin; Connectors, OAuth flows, and vendor API changes require constant upkeep.; Model quality and inference operations are part of the product.
What do I still own after building a Grammarly alternative?
Secure credentials, rotate secrets, and handle provider rate limits. Run migrations, backups, restores, and dependency updates. Test the critical journey after every model, API, or hosting change. Monitor failures and fix the edge cases a first prompt will miss. Maintain every third-party integration as APIs and OAuth rules change.