Do Metal Detecting Sites Block AI Crawlers? 3 of 7 Do

Among the metal detecting sites we checked, the split is almost even: a little under half of those with a published policy turn an AI crawler away at the door. Of the 10 metal detecting sites in this snapshot, 7 returned a parseable robots.txt, and 3 of those block at least one AI crawler — a 42.9% block rate.

That puts a niche treasure-hunting hobby almost on par with how Fashion and Running sites gate the crawlers, and it sits a touch above the corpus as a whole. This is a sealed, point-in-time read of public robots.txt files, not a survey of opinions or a forecast of where the hobby is heading.

3 of 7 Metal Detecting sites block at least one AI crawler.

A robots.txt file is the plain-text instruction sheet a website publishes to tell automated crawlers which paths they may fetch. When a site adds a token like User-agent: GPTBot followed by Disallow: /, it is asking that specific AI crawler to stay out. Whether the crawler honors the request is a separate question we address below.

Which Metal Detecting Sites Gate the Crawlers

The three blockers in this snapshot are detectorprospector.com, minelab.com, and treasurenet.com — a mix of an enthusiast prospecting hub, a detector manufacturer, and one of the hobby's largest forums. They each published a robots.txt that disallows at least one named AI user-agent.

The sites that returned a robots.txt and allow every AI crawler are metaldetectingforum.com, kellycodetectors.com, garrett.com, and noktadetectors.com. Two of those are detector brands and one is a major retailer, so a permissive policy is not unusual for a vendor that wants its catalog discoverable.

Three named sites — detectorprospector.com, minelab.com, and treasurenet.com — each disallow at least one AI user-agent.

Three more sites — findmall.com, fisherlab.com, and bountyhunteronline.com — returned no parseable robots.txt at all. A missing file is not a block; it simply means no crawl preference is published, so a crawler reads it as open by default.

Where Metal Detecting Sits Among Similar Hobbies

At 42.9%, metal detecting shares its exact block rate with Fashion, Running, and Surfing — the cluster of categories sitting just below the mid-pack. Directly above it, Cosplay and Bonsai both post a 44.4% rate, while Social, Sports, Fitness, and Photography sit just below at 40%. The window below is metal detecting and its nearest neighbors in the ranking. For a category at the permissive end of this same spectrum, where no site names any of these operators, see the prepping report on AI-crawler policies.

For context at the extremes, Gaming leads the entire ranking at 88.9% and News follows at 81.3%, while categories such as Prepping and Pottery post a 0% block rate. Metal detecting lands much closer to the middle than to either edge.

The shared 42.9% across Fashion, Running, Surfing, and Metal Detecting is a coincidence of small samples, not a pattern with a single cause. Each of those four categories had 7 sites return a parseable file and 3 of them gate, so the rate matches even though the motives differ — fashion guards lookbook imagery, running guards training and gear content, and metal detecting guards find logs. The neighbors above, Cosplay and Bonsai at 44.4%, have one more gating site each out of nine, which is all that separates the two tiers.

Metal Detecting sites post a 42.9% AI-crawler block rate.

What This Block Rate Actually Means

The corpus baseline is the right yardstick here. Across all 867 sites with a parseable robots.txt, 260 block at least one AI crawler — a 30% rate. Metal detecting sits above that line, which is mildly surprising for a hobby with no obvious commercial stake in gating model training.

A plausible read is that the hobby's content centers on detailed find logs, location notes, and equipment reviews — the kind of original, hard-won material a contributor might not want absorbed silently into a model. The brand-and-retailer sites lean permissive because discoverability sells detectors; the forum and prospecting hub lean protective because the community wrote the content.

It is worth being precise about what the 42.9% does and does not say. It is a count of sites with a published, parseable file that disallows at least one AI user-agent — not a measure of how many pages are protected, nor of how strictly. A site that blocks a single bot and a site that disallows every AI crawler both count once here. The figure captures the decision to gate, which is the leading edge of how a vertical thinks about AI access.

Corpus-wide, 260 of 867 sites with a published policy block at least one AI crawler.

The mix of blocker types also matters. Two of the three gaters — detectorprospector.com and treasurenet.com — are community destinations, while minelab.com is a manufacturer. That a brand sits among the blockers is the more notable detail: vendors usually want maximum discoverability, so a manufacturer choosing to disallow an AI crawler suggests a view that its product pages, manuals, or imagery are worth withholding from at least one model pipeline.

Who Gets Disallowed Most Across the Corpus

The block decisions above are about specific operators, and corpus-wide the order is consistent. The focused cut below shows the most-disallowed operators across all 867 sites — Common Crawl, whose archive feeds many downstream models, tops the list.

Common Crawl draws the most disallow tokens, with Anthropic and OpenAI close behind. A metal detecting site that blocks "an AI crawler" is most often naming one of these operators rather than a long-tail bot. For the same pattern viewed inside other enthusiast verticals, see how it plays out in the cosplay AI-access report and the bonsai crawler-blocking breakdown, both of which sit just above metal detecting in the ranking.

The operator view is useful because it explains the shape of the corpus baseline. A site rarely targets one bot in isolation; the same publishers that disallow Common Crawl tend to disallow Anthropic and OpenAI in the same file, which is why the top operators cluster so tightly at 194, 184, and 175.

The further down the list — Apple at 131 and below — the more selective the disallow decision tends to be.

How the Snapshot Was Sealed

Every figure here is a verbatim count from a sealed snapshot of public robots.txt files, captured 14 June 2026 and content-addressed with the sha 4247236167461a45. We fetch the file each site publishes, parse the AI user-agent tokens it disallows, and seal the result; nothing is estimated, modeled, or extrapolated. A site with no parseable file is recorded as exactly that — not as a block and not as a guess.

The wider edition behind this category covers 1038 sites overall, 867 of which returned a parseable robots.txt, grouped into 104 content categories. The llms.txt signal — a newer file some publishers use to express AI preferences — appeared on 216 sites, or 24.9% of those with robots.txt.

Because the snapshot is content-addressed, the result is reproducible: anyone can re-fetch the same files and compare. That is the point of sealing rather than re-querying live — a live check would drift as sites edit their files, while the sealed count is fixed to 14 June 2026. For metal detecting, that fixed reference means the next snapshot can show, site by site, exactly which of the 7 with a policy changed their stance.

Frequently Asked Questions

Q: Which metal detecting sites block AI crawlers in this snapshot?

A: Three sites — detectorprospector.com, minelab.com, and treasurenet.com — each disallow at least one AI user-agent in their published robots.txt. The other four sites with a parseable file (metaldetectingforum.com, kellycodetectors.com, garrett.com, and noktadetectors.com) allow every AI crawler.

Q: Why do some metal detecting sites show no result at all?

A: Three sites — findmall.com, fisherlab.com, and bountyhunteronline.com — returned no parseable robots.txt. That is neither a block nor an allow; it simply means the site publishes no crawl preference, which most crawlers read as open access by default.

Q: Is a 42.9% block rate high for a hobby category?

A: It is above the corpus baseline. Across all 867 sites with a policy, the rate is 30%, so metal detecting gates AI crawlers somewhat more than the typical site — and it sits level with Fashion, Running, and Surfing at 42.9%.

Q: Does adding a crawler to robots.txt actually stop it?

A: Not by force. robots.txt is an honor-system standard: compliant crawlers read the file and respect the disallow, but it is a published request, not a technical barrier. The 3 of 7 figure measures stated intent in the file, not enforced exclusion.

Q: Why does a detector manufacturer like minelab.com block when other brands do not?

A: The data shows the choice, not the reason — minelab.com disallows at least one AI user-agent while garrett.com and noktadetectors.com allow all. A vendor that gates is signaling it sees its product pages, manuals, or imagery as content to protect, where the more permissive brands prioritize being found by AI assistants.

Put AI-Access Data to Work

The first buyer for this data is an AI-search or GEO agency tracking which client-eligible corpora remain crawlable. Such a team would re-crawl the metal detecting set on a weekly cadence and trigger an alert the moment a permissive site — say garrett.com or noktadetectors.com — adds a new AI user-agent token to its disallow list, because that single change can drop a client's pages out of an answer engine's reach.

A category-native buyer fits second: a detector-retail ecommerce buyer monitoring whether competitor catalogs at minelab.com or kellycodetectors.com stay visible to AI shopping assistants. US Tech Automations runs that monitoring as scheduled robots.txt and llms.txt crawls with change alerts on named domains. See how the workflow is built on the agentic workflows platform.

Corpus-wide, 260 of 867 sites block at least one AI crawler.

Key Takeaways

• Of 10 metal detecting sites, 7 returned a parseable robots.txt and 3 of those block at least one AI crawler — a 42.9% rate.

• The blockers are detectorprospector.com, minelab.com, and treasurenet.com; the named allowers are metaldetectingforum.com, kellycodetectors.com, garrett.com, and noktadetectors.com.

• The category sits above the 30% corpus baseline and level with Fashion, Running, and Surfing.

• Common Crawl draws the most disallow tokens corpus-wide at 194, with Anthropic at 184 and OpenAI at 175.

Source: US Tech Automations Research — Closing Web edition; figures are verbatim counts from public robots.txt files sealed June 14, 2026 (snapshot sha 4247236167461a45).