PostGenie

Turn a public webpage, text-based PDF, or pasted text into an AI-assisted draft for LinkedIn, X, or both.

Choose a tone and length, optionally add hashtags or a call to action, then review the result and copy it. PostGenie does not publish to your accounts.

URLs, PDFs, or text
LinkedIn and X
Review, then copy
  1. 1Add readable source content
  2. 2Choose platform and options
  3. 3Review and copy the draft

Input Content

Target Platform

Generated Posts

Ready for your source

Generated drafts will appear here for review.

How it works

From source material to a reviewable draft

  1. 1. Provide a source

    Enter a public HTTP or HTTPS URL, upload a text-based PDF, or paste text directly.

  2. 2. Set the output

    Choose LinkedIn, X, or both, then select tone, length, hashtags, and call-to-action options.

  3. 3. Review and copy

    The generated draft appears with a character count. Check it for accuracy, copy it, and edit it where you plan to publish.

Supported inputs and outputs

What the generator handles

Inputs

  • Public webpages: readable HTML or plain text over standard HTTP or HTTPS ports; extraction uses up to 3,000 characters.
  • PDFs: text-based files up to 8 MB and 50 pages; generation uses up to 12,000 extracted characters.
  • Pasted text: notes, article copy, or other text up to the generator's 12,000-character request limit.

Outputs and controls

  • One LinkedIn draft, one X draft, or one draft for each platform when "both" is selected.
  • Professional, casual, engaging, or educational tone; short, medium, or long length.
  • Optional hashtags and call to action, plus a character count and copy button.
  • Draft creation only: there is no account connection, scheduling, or direct publishing workflow.

Realistic use cases

Useful starting points, not autopilot

Summarize a public announcement for a professional network.

Pull shareable highlights from a text-based report or brief.

Adapt the same source into LinkedIn and shorter X drafts.

Turn internal notes into a first draft for editorial review.

Illustrative example — fictional, not a customer result

A source excerpt turned into platform drafts

Actual wording varies. This example shows the kind of transformation the generator is designed to make.

Fictional source excerpt

“Example Community Library will add Saturday hours beginning September 7. The pilot runs for three months and includes free digital-skills workshops.”

Illustrative LinkedIn draft

Example Community Library is expanding Saturday access starting September 7. The three-month pilot also adds free digital-skills workshops—a practical step toward making local resources easier to use. Which workshop topics would be most useful to your community? #Libraries #DigitalSkills

Illustrative X draft

Example Community Library adds Saturday hours Sept. 7, plus free digital-skills workshops during a three-month pilot. What topic should they teach first? #Libraries

Data handling

What the implementation shows

  • URLs are fetched by the app server, PDFs are uploaded for server-side text extraction, and pasted text is submitted to the server.
  • Source text and selected options are sent to the configured Azure OpenAI endpoint to create the draft.
  • The generator routes do not write source text or generated drafts to a database or user account; the interface keeps the result in current page state.
  • Google Analytics loads on the page. Its custom successful-generation event contains input type, selected platform(s), and post count—not source or generated text.
  • A one-hour HTTP-only session cookie is set to support request validation. The code does not define provider retention, so no broader retention promise is made here.

Limitations

Review before you publish

  • AI-generated drafts can omit context, misstate details, or use wording that does not fit your voice. Verify facts and edit the result.
  • URL extraction is heuristic. Paywalled, login-only, script-heavy, oversized, non-text, or inaccessible pages may fail or return incomplete text.
  • Scanned or image-only PDFs may not produce text because the PDF workflow does not perform OCR.
  • Only LinkedIn and X drafts are supported. X output is capped at 280 characters; the app does not publish or schedule posts.
  • Requests are rate-limited, so repeated generation or upload attempts may be temporarily blocked.

FAQ

Common questions

Does PostGenie post to LinkedIn or X?

No. It creates a draft in the browser for you to review and copy.

Can it generate for both platforms?

Yes. Selecting both runs separate generation requests and returns one LinkedIn draft and one X draft.

Why did a webpage or PDF fail?

The source may be private, unreadable, too large, image-only, or outside the supported URL and PDF limits.

Is the output guaranteed to be accurate?

No. Treat it as a first draft and compare important claims with the source before publishing.

Does the generator save my content?

The app routes do not persist source text or drafts to an account or database, but source text is sent to Azure OpenAI for generation. No provider-retention claim is made.

Does it preserve the source formatting?

No. Extraction normalizes text, and the model writes a new platform-specific draft rather than reproducing the original layout.