VQV Signal

OPEN SOURCE WATCH TECHNICAL

Mintlify open-sources agent-traffic, a classifier for AI agent requests

According to a post on X by @mintlify, Mintlify released agent-traffic, the dataset and classifier it uses to identify which agent, crawler or person is behind each request. The company says agents made 489M requests to Mintlify-hosted docs last month. The tool covers 98 agents and crawlers, verifies crawlers against published IP ranges, and catches agents that hide behind browser user agents. The source snippet is cut off before its full explanation of the benefits for site owners.

Source: Scobleizer News Pulse (X) · x.com Found via Robert Scoble’s Scobleizer News Pulse · a post on X, not independently verified Published 2026-11-10T20:40:00+00:00 Detected 2026-11-11T02:17:19+00:00
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According to a post on X by @mintlify, Mintlify released agent-traffic, the dataset and classifier it uses to identify which agent, crawler or person is behind each request. The company says agents made 489M requests to Mintlify-hosted docs last month. The tool covers 98 agents and crawlers, verifies crawlers against published IP ranges, and catches agents that hide behind browser user agents. The source snippet is cut off before its full explanation of the benefits for site owners.

AI-assisted summary based on the listed source.

Mintlify released agent-traffic, the dataset and classifier it uses to tell which agent, crawler or person is behind each request; it says agents made 489M requests to Mintlify-hosted docs last month. The tool covers 98 agents and crawlers, verifies crawlers against published IP ranges and catches agents hiding...

Site owners and documentation teams could use this kind of classifier to see how much of their traffic comes from AI agents rather than people. Builders who run docs or websites may be able to check whether crawlers are who they claim to be, and agents disguised as browsers are harder to spot without such tools. The source does not give more detail, so it is worth watching for the full release and how the classifier performs in practice.

Signal Strength 95% Technical label WATCH Public Interest 44 Category OPEN SOURCE Reader Depth TECHNICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 0 Practical Impact Score 74 Novelty Interest Score 94 Consequence Score 18 Curiosity Score 16 Shareability Score 58

VQV surfaced this signal because it is recent, relevant to AI Agents, connected to Scobleizer News Pulse (X).