LLMagnet
Article editing for LLM citation
Score citeability. Pressure-test the news cycle. Edit for machines without killing the story.
What you’ll notice
Load a sample story — or edit the headline and body yourself. One draft stays with you through every editing step.
Eight sample pieces ready to run.
A clear score for how likely answer engines are to quote you — plus why, in plain English.
Two editors argue: human reader vs AI discoverability.
We pull Google, similar coverage, and X — then hold your draft up against what’s circulating today.
Every source shows the site it came from.
Clear next moves before you touch the text — then a simple ask: ready to polish without losing your voice?
Advice ranked by impact, not jargon.
We densify facts from the web, keep your tone, and return a fuller rewrite plus a plain list of what was added.
Clean polished copy · bullet list of what changed.
We find and read competing articles, then flag the angles and facts they have that you don’t.
Walk out knowing exactly what to report next.
How editing works here
Paste or import a URL. That article becomes the single working copy for the whole flow.
Get a citability score, then check Google and X so you know if you’re behind the news cycle.
Accept the rewrite, then see what rival coverage still has on you — and fix it.
Why not just ChatGPT?
OpenAI and Claude are excellent general models. LLMagnet is a specialized editorial product for making news articles more citeable — often powered by those same models under the hood.
| Capability | LLMagnet | OpenAI ChatGPT | Claude |
|---|---|---|---|
| Built for newsroom article editing | Yes — draft → score → live → advice → polish → rivals | Blank chat | Blank chat |
| Citeability score for answer engines | Live probe + E-E-A-T matrix | No product score | No product score (rarely cites) |
| Live news / X / Reddit pressure-test | Built into Live check | Needs custom tooling | Needs custom tooling |
| Context carries across edits | Score + live + advice feed the next prompt | Manual re-paste | Manual re-paste |
| Rival coverage gap analysis | Scrapes other outlets vs your draft | DIY research | DIY research |
FAQ
Whether an answer engine would lift a sentence from your piece when answering a user — denser claims, named entities, attribution, and extractable structure.