How the ToolSignal pipeline works

ToolSignal runs a fully automated editorial pipeline. We publish this methodology because readers deserve to know exactly how the content they read is produced.

1. Signal collection

Every hour-scale cycle, the system polls Google Trends trending-search feeds for eight countries (US, GB, CA, AU, IN, DE, SG, NZ) and stores each trending topic with its approximate traffic and the news reporting attached to it.

2. Opportunity filter

Each topic is scored on relevance to our beat (AI, software, consumer tech), search volume, and query intent. A hard-coded blocklist rejects YMYL-sensitive topics (medical, financial advice, gambling), adult content and celebrity-privacy topics outright — no exceptions, no override.

3. Source-grounded drafting

For topics above threshold, an AI model drafts an article under strict rules: it may only assert facts present in the attached news sources or universally known stable facts; every section must open with a direct answer; uncertainty must be stated, not papered over.

4. Independent automated review

A second, independent AI model reviews each draft against its sources. It fails any draft that asserts prices, dates, specs or quotes not supported by the sources, and any draft that merely restates headlines without reader value. Drafts scoring below 7/10 are rejected and archived — visibly logged, never published.

5. Publication limits

The pipeline publishes at most a small fixed number of articles per day (currently 2). This is a deliberate quality-over-volume constraint: we would rather publish two well-sourced pieces than fifty thin ones.

AI disclosure

Articles are drafted with AI assistance and reviewed automatically; this is disclosed on every article page. Launch-day reference articles were additionally fact-checked against primary sources on the verification date shown in each article.

Corrections

If a published fact is wrong, we correct the article and note the correction. See our corrections policy.