How is this different from a simple read-time shortener?

Read-time shorteners cut sentences; summarization distills meaning. Our tool reads the full article, identifies the thesis, organizes supporting arguments, and rewrites them in ~150-word form. In our benchmark (n=400 articles, 3 editor reviewers), our summaries rated 4.7/5 for faithfulness vs. 3.1/5 for extractive (first-paragraph) shorteners.

Can I summarize paywalled or login-gated articles?

No — we fetch only publicly accessible content. For gated articles, paste the full text instead of the URL and the tool works the same way. Respect the publisher's terms when copying content.

What article length does this support?

Up to 15,000 characters of text (~3,000 words) or any publicly reachable URL. For longer articles, split into sections and summarize each. Very short articles (<200 words) return thin summaries — the tool needs enough signal to extract meaningful points.

Is summarization legal under copyright?

Yes. Summarization is explicitly fair use in most jurisdictions (US, EU, UK, India) when the summary is original prose, credits the source, and doesn't reproduce substantial verbatim text. Our tool rewrites rather than quotes — outputs are 95%+ novel against source.

Do summaries degrade on technical content?

Slightly for math-heavy or jargon-dense papers. Scientific, medical, and legal papers retain terminology but can oversimplify dependencies. Always cross-check the summary against the source before citing. For peer-reviewed research, use summaries as navigation aids, not replacements.

How does this differ from ChatGPT summaries?

Functional outputs are similar, but our tool is built for workflow speed: paste URL → summary in under 3 seconds, no chat context to manage, no tokens to count, structured output (summary + bulleted key points), no signup. Good for batch work where you scan 20 articles for one research task.

Are my inputs stored or used for training?

No. URLs are fetched server-side, content processed in memory, summary returned, source discarded. Nothing is logged or used for model training.

Does Google penalize AI-summarized content?

Google's guidelines target scaled, low-effort AI content. A summarized excerpt with original commentary, credit to the source, and genuine editorial value is fine. Republishing AI summaries as standalone articles without context is not. Use summaries as input for your own writing, not as output.

Can I summarize multiple articles at once?

Not in bulk yet — one URL or block of text per request. For bulk research workflows, use Grigora's full content-curation CMS which supports batch ingestion, tagging, and newsletter-ready digests.

What languages are supported?

English is primary. Spanish, French, German, Italian, Portuguese, Dutch, Hindi work well. Mixed-language inputs produce inconsistent summaries.

Can summaries be used in newsletters or roundups?

Yes — this is a common use case. Generate summary, rewrite in your editorial voice, link back to the original. Many newsletters (Tldr, Hacker Newsletter, Benedict's Newsletter) operate on this model at scale.

Article Summary Tool

Paste a URL or text. Get TL;DR + 3-6 key points in under 3 seconds. Perfect for research, curation, and newsletters.

4.6/5 on G2 4.8/5 on Trustpilot

286K+

Articles summarized

~3s

Avg. summary time

15K

Char input ceiling

4.8/5

User rating

How to summarize any article

Three steps. No editor install. No chat context to manage.

Paste URL or text

Switch between URL and text modes depending on source.

AI summarizes

TL;DR + 3-6 key points extracted in under 3 seconds.

Copy or download

Clipboard, text file, or markdown-paste into Notion, Substack, Obsidian.

Original Grigora research

Summary faithfulness vs. method

3 editors blind-rated summaries from 400 articles across 6 domains (news, finance, tech, health, research, marketing) on a 5-point faithfulness scale.

Grigora (abstractive AI)

4.7/5

4.7/5 — best faithfulness

ChatGPT default prompt

4.4/5

4.4/5 — inconsistent structure

TLDR This (free tier)

3.7/5

3.7/5 — extractive, terse

Extractive (first-paragraph)

3.1/5

3.1/5 — misses buried leads

Manual one-sentence

2.9/5

2.9/5 — oversimplifies

Source: Grigora benchmark, 3 editors × 400 articles × 5 methods, Feb 2026. 5-point Likert.

Platform-specific workflows

Plug summaries into the workflow you already run.

Newsletter writing (Beehiiv / Substack)

1.Collect 8-12 article URLs each week.
2.Summarize each, copy output into your draft.
3.Rewrite in your voice, add original commentary, link back.

Research (Notion / Obsidian)

1.Create a "Sources" database with URL + summary + notes columns.
2.Paste each summary into the summary field.
3.Use the structured output for literature mapping and citation.

Slack / Teams curation

1.Bookmark interesting articles.
2.Summarize before sharing to team channels.
3.Post "TL;DR + link" to respect colleagues' time.

Competitive intel dashboards

1.Pull competitor blog RSS or manual URLs.
2.Summarize each into a structured record.
3.Tag by topic, hook, and angle for editorial planning.

Client reporting

1.Summarize industry articles weekly.
2.Bundle into a "what happened in your space" digest.
3.Send to clients as value-adds to retainer work.

Who uses article summaries

Six real workflows with the measurable outcome each reports.

Researchers

Scan 20 papers in 30 minutes instead of 10 hours. Pull citations, thesis, and method from each.

20x faster lit reviews

Newsletter curators

Digest 50 industry articles into a weekly roundup. Paste URLs, extract summaries, rewrite in your voice.

Curator productivity +6x

Content marketers

Analyze competitor blog posts at scale. Extract angles, hooks, and topic gaps for your editorial plan.

Content audits 10x faster

Students

Pre-read assigned articles, extract key arguments, then do deep reading on the ones that matter.

Study time cut 40%

Journalists

Rapidly triage breaking news. Scan 30 sources in minutes to find the exclusive angle worth chasing.

Breaking coverage first

Execs / analysts

Get the gist of long industry reports or earnings transcripts during your commute.

Informed in 5 min

Common summary mistakes & quick fixes

Eight failure modes and the fix for each.

Summary is vague ("the article discusses...")

Fix: The AI couldn't identify a clear thesis — often because the source is a listicle or news roundup. Try the tool with a more focused article, or paste a specific section instead of the whole page.

Key points are generic / repeat the summary

Fix: The source likely has only one real point, padded with fluff. This is a source-quality issue, not a tool issue. Check if the article is genuinely substantive.

URL fetch failed

Fix: The URL is behind a paywall, requires login, or has strict anti-scraping protection. Paste the article text directly instead.

Summary misses the main argument

Fix: Buried leads confuse AI. If the thesis is in paragraph 8, the summary may focus on the intro. Paste a shorter version (the argument-containing section) for better results.

Technical terms got oversimplified

Fix: Standard with first-pass AI on specialist content. Always cross-check against source before citing. For medical/legal/scientific content, treat summaries as navigation, not replacement.

Summary is longer than the source

Fix: Very short inputs produce proportionally inflated outputs. For <300-word sources, summarization adds no value — read directly.

Numbers or dates are wrong

Fix: AI can paraphrase statistics incorrectly. Always verify numerical claims against source. Flag "roughly", "about" in the summary — they indicate the model's uncertainty.

Summary sounds biased vs. source

Fix: Rare, but the AI can amplify the article's existing slant. Read both the source and summary; rewrite in your voice if publishing.

Grigora vs. TLDR This vs. SummarizeTech

Feature-by-feature comparison of the three most-used summarizers.

Feature	Grigora	TLDR This	SummarizeTech	Note
URL + text input both				SummarizeTech is YouTube-only.
Free unlimited				TLDR This: 10/day free. SummarizeTech: 5/day free.
No signup required				Paste URL, read summary, leave.
Summary + bulleted key points				All three produce structured outputs.
Markdown-formatted output				Paste directly into Notion, Substack, Obsidian.
15K char input ceiling				Competitors cap at 4-8K.
Input privacy (no training)				TLDR This and SummarizeTech retain inputs for model training.
12+ language support				English strongest in all three.

Optimized for AI Overviews, Perplexity, ChatGPT

Built for AI-search workflows

Summary outputs are structured for direct paste into LLM contexts. Metadata preserved. Citations intact.

Structured schema

SoftwareApplication, FAQPage, HowTo, Breadcrumb, ItemList embedded.

Markdown output

Paste into Notion, Substack, Obsidian, Claude, ChatGPT with preserved formatting.

Citable sources

Original research on summarization methods gives AI engines a stable source to cite.

From summary to publication — one tool

Grigora is the no-code SEO-first CMS. Summarize, curate, remix, and publish to your domain inside one editor.

AI editor

Summarize, expand, rephrase, pivot — 20+ actions in-post.

Auto-SEO

Schema, sitemaps, meta handled. Just write.

No-code

Drop blocks, style inline, publish to your domain.

Start free

Frequently asked questions

Every question users ask before their first summary.

Paste a URL or long-form text, and AI returns a concise summary plus 3-6 bulleted key points. Lets you skim a 2,000-word article in 20 seconds without losing the thesis. Handles blog posts, news, research papers, and marketing pages.

Reviewed by the Grigora editorial team · Last updated May 2026

Benchmarks come from the Feb 2026 summary faithfulness study — 3 senior editors × 400 articles × 5 methods, rated on a 5-point Likert scale across news, finance, tech, health, research, and marketing domains.

URLs and text are processed in-memory and discarded. Nothing is stored or used for training.