Can PromptDC be vibe coded?
Rewrite selected text or turn vague coding requests into implementation-ready prompts from any website.
A useful personal version is highly one-shot-able: an MV3 content script can capture selected text, send it to an LLM with one of two system prompts, then replace a normal editable field or copy the result. The commercial product earns its keep through Writing profiles (grammar fix, email, social post, shorten, tone), a Coding mode that auto-detects which AI tool you are prompting and tailors the rewrite, polished interaction design, and defensive handling of complex editors where naive DOM replacement can fail or corrupt text.
Jump to the build brief ↓Checked Jul 2026
What you pay today, before any DIY hosting
high 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
- Select text, choose Writing or Coding, call an LLM with the matching rewrite prompt, then replace the selection or copy the result.
- 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
- Writing profiles tuned for grammar fix, email replies, social posts, shortening, and tone
- Coding mode platform detection that tailors the rewrite to the AI tool you are prompting (ChatGPT, Claude, Cursor, Lovable and more)
- Reliable behavior across Gmail, LinkedIn, Google Docs, Shadow DOM, and framework-managed rich text editors
- Cloud accounts, usage credits, profile sync, and a managed billing flow
- The last 20 percent is sync, migration fidelity, speed, and edge cases.
Why people still pay
People pay for confidence that rewriting works across the sites and editors they use every day, plus maintained profiles, a polished interface, account features, and fixes when web apps change. A personal BYOK clone covers the basic loop well, but keeping rich editors reliable is continuing product work.
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 PromptDC
Context
**PromptDC** — Rewrite selected text or turn vague coding requests into implementation-ready prompts from any website. It currently costs $9/mo.
A useful personal version is highly one-shot-able: an MV3 content script can capture selected text, send it to an LLM with one of two system prompts, then replace a normal editable field or copy the result. The commercial product earns its keep through Writing profiles (grammar fix, email, social post, shorten, tone), a Coding mode that auto-detects which AI tool you are prompting and tailors the rewrite, polished interaction design, and defensive handling of complex editors where naive DOM replacement can fail or corrupt text.
This brief describes a focused, single-operator replacement for the part of PromptDC 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
Select text, choose Writing or Coding, call an LLM with the matching rewrite prompt, then replace the selection or copy the result.
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
Chrome developer mode with Load unpacked.
Data and integrations
OpenAI or Anthropic API key.
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 Chrome extension for rewriting selected text with an LLM.
Use Manifest V3, vanilla HTML, CSS, and JavaScript, with no framework, bundler, package manager, or build step.
Create manifest.json, background.js, content.js, content.css, options.html, options.js, and simple generated placeholder icons.
Request only storage, contextMenus, activeTab, and scripting permissions, plus host permissions for the chosen LLM API.
Add an options page that stores provider, API key, and model in chrome.storage.local, never chrome.storage.sync.
Support OpenAI and Anthropic through direct fetch calls from the background service worker.
Use the OpenAI Responses API or Chat Completions API and the Anthropic Messages API with correct headers and response parsing.
Never log the API key or selected text, and show clear errors for a missing key, HTTP failure, rate limit, or malformed response.
Provide exactly two modes: Writing and Coding, with the last choice saved locally.
Writing mode must offer selectable profiles: Improve, Grammar fix, Shorten, Email, Social post, and Tone, each with its own system prompt that preserves facts and meaning, matches the input language, and returns only the revised text.
Coding's system prompt must turn a vague request into an implementation-ready specification with goal, context, requirements, constraints, acceptance criteria, and likely files, while preserving user intent and returning only the enhanced prompt.
Create a context menu named Enhance selected text that works on selection and editable contexts.
Also inject a small accessible floating button beside any nonempty text selection after mouseup or keyboard selection.
The floating UI must include a compact mode selector with the Writing profiles and Coding, an Enhance button, a loading state, and a dismiss control.
Capture selections in input and textarea elements with selectionStart and selectionEnd, and capture contenteditable selections with a cloned DOM Range.
For input and textarea, replace only the captured range, preserve surrounding text and caret position, and dispatch bubbling input and change events.
For contenteditable, restore the saved Range, replace only its contents with a text node, dispatch a bubbling input event, and avoid innerHTML assignment.
If the selection is read-only, detached, stale, or cannot be safely replaced, copy the result with navigator.clipboard.writeText and show a small Copied notification.
If no selection exists in an editable field, enhance the field's full current value; otherwise show a helpful Select some text message.
Pass requests from the content script to the service worker with chrome.runtime.sendMessage so page scripts never receive the API key.
Keep the interface unobtrusive, keyboard accessible, responsive, and isolated with prefixed CSS class names and a high z-index.
Include an options-page Test API button and a concise README with Load unpacked instructions, provider setup, security caveats, and a manual test checklist.
Handle extension reloads and restricted chrome:// pages gracefully, and remove injected UI when the selection collapses or Escape is pressed.
Deliberately leave out accounts, sync, per-site profiles, billing, telemetry, analytics, history, and any backend server.
Return every file with finished code, not pseudocode or TODOs, so loading the folder as an unpacked extension works immediately.
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:
Writing profiles tuned for grammar fix, email replies, social posts, shortening, and tone.
Coding mode platform detection that tailors the rewrite to the AI tool you are prompting (ChatGPT, Claude, Cursor, Lovable and more).
Reliable behavior across Gmail, LinkedIn, Google Docs, Shadow DOM, and framework-managed rich text editors.
Cloud accounts, usage credits, profile sync, and a managed billing flow.
The last 20 percent is sync, migration fidelity, speed, and edge cases.
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.
Risk
**Manageable.** A personal version is realistic if you test the critical journey and keep reliable backups.
Editorial confidence in this assessment: high. No independent one-shot implementation is linked yet.
Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/promptdc
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.
Before you start
Can PromptDC be vibe coded?
Yes, for personal use. A useful personal version is highly one-shot-able: an MV3 content script can capture selected text, send it to an LLM with one of two system prompts, then replace a normal editable field or copy the result. The commercial product earns its keep through Writing profiles (grammar fix, email, social post, shorten, tone), a Coding mode that auto-detects which AI tool you are prompting and tailors the rewrite, polished interaction design, and defensive handling of complex editors where naive DOM replacement can fail or corrupt text.
What can an AI coding agent reproduce from PromptDC?
Select text, choose Writing or Coding, call an LLM with the matching rewrite prompt, then replace the selection or copy the result. 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 PromptDC replacement still be missing?
Writing profiles tuned for grammar fix, email replies, social posts, shortening, and tone; Coding mode platform detection that tailors the rewrite to the AI tool you are prompting (ChatGPT, Claude, Cursor, Lovable and more); Reliable behavior across Gmail, LinkedIn, Google Docs, Shadow DOM, and framework-managed rich text editors; Cloud accounts, usage credits, profile sync, and a managed billing flow; The last 20 percent is sync, migration fidelity, speed, and edge cases.
What do I still own after building a PromptDC 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.