Billion-Dollar Weather Disasters Database Returns, Reveals $100B+ Losses

This post explains what to do when an automated system cannot retrieve an article from a URL and requests that you paste the article’s content.

Drawing on three decades in scientific communication and information systems, I outline why retrieval fails, how to prepare and paste text for accurate AI summarization, and what to expect from a condensed 10-sentence summary.

Table of Contents

Why automated URL retrieval sometimes fails

Automated systems that fetch web pages are powerful, but they are not omnipotent.

They often encounter technical, legal, or format-related barriers that prevent them from accessing the raw text behind a URL.

Common causes of retrieval errors

Understanding why a fetch failed helps you provide the best fallback: the article text itself.

Below are typical reasons systems return a request to paste content manually.

Paywalls and authentication: Many journal sites require logins or subscriptions that bots cannot bypass.

Robots.txt and API limits: Sites can block automated scraping through site rules or rate limits.

Dynamic content: Pages rendered client-side with JavaScript may not expose static text to simple fetchers.

Network errors and redirects: Broken links, redirects, or temporary outages can interrupt retrieval.

File formats: PDFs or embedded documents can be harder to parse automatically.

How to share content for effective AI summarization

If a retrieval fails, pasting the article’s content is the most reliable option.

Follow a few simple practices so the AI can create an accurate and useful summary.

Best practices when pasting text

These steps help preserve context and ensure the summary reflects the original article faithfully.

Paste the full text: Include the complete article body—headlines, subheadings, and bylines if present.

Include the URL and citation: Even if the fetch failed, provide the source for traceability and credibility.

Note the desired output: Specify “summarize into 10 sentences” or another format to guide the AI.

Remove sensitive data: Redact personal information or proprietary content you cannot share.

Specify language and tone: If you need a neutral scientific tone or a layperson-friendly summary, say so.

What you can expect from an AI-produced 10-sentence summary

An expert-crafted 10-sentence summary highlights the most important facts while remaining concise.

The goal is clarity, not exhaustive coverage, so some nuance will be compressed.

How I (as the summarizer) approach the task

When I convert an article into 10 sentences, I prioritize the main hypothesis, key methods or evidence, primary results, and implications.

I will:

Extract the central thesis: One or two sentences identify the core message.

Summarize methods and evidence: A couple of sentences capture the approach used and the strength of evidence.

Convey key results: Two to three sentences state the findings succinctly.

Note implications and limitations: One or two sentences put the results into context and flag uncertainties.

Privacy, copyright, and workflow considerations

Before pasting content, consider privacy and copyright.

Publicly available articles are typically fine to share for summarization, but personal data and copyrighted material may require additional caution.

Quick checklist before you paste

Use this checklist to make the process smooth and compliant:

Confirm you have the right to share the text.

Remove or anonymize sensitive details.

Provide a clear instruction for summary length and emphasis.

Mention any specific audience or tone preferences.

If an automated retrieval returns the message asking you to paste the article, don’t worry—this is a routine fallback.

Paste the article text, include the URL and any special instructions, and I will produce a focused, 10-sentence summary that highlights the most important details while noting caveats and context.

If you prefer, I can also create alternative formats: bullet-point highlights, lay summaries, or an executive abstract for different audiences.

Here is the source article for this story: Trump ‘retired’ a database tracking the most expensive weather disasters. Now it’s back — and finding over $100B in losses