How AI assistants fetch web pages: Nginx log analysis of ChatGPT, Claude, Gemini and others

A developer conducted a practical experiment to determine whether AI assistants fetch web pages live or answer from cached indexes when users ask about specific sites. By setting up custom Nginx logging and prompting major chatbots with unique query strings, they captured clear evidence of retrieval behavior.
The probe setup
The test used a custom Nginx log format to capture headers that the default combined log compresses:
log_format ai_probe escape=json '{' '"time":"$time_iso8601",' '"ip":"$remote_addr",' '"uri":"$request_uri",' '"status":$status,' '"ua":"$http_user_agent",' '"referer":"$http_referer",' '"accept":"$http_accept"' '}';
Each assistant received a prompt pointing to a unique query string (/?ai=chatgpt, /?ai=claude, etc.), making attribution straightforward. Prompts were rerun across sessions to avoid transient cache hits masking retrieval patterns.
Who announced themselves with dedicated user-agents
Five assistants arrived with retrieval-specific signals:
- ChatGPT: ChatGPT-User/1.0 (Chrome-style Accept, no robots.txt check)
- Claude: Claude-User/1.0 (*/* Accept, always checks robots.txt first)
- Perplexity: Perplexity-User/1.0 (empty Accept header)
- Meta AI: meta-webindexer/1.1 (*/* Accept, no robots.txt check)
- Manus: Manus-User/1.0 suffix on Chrome UA (Chrome-style Accept)
All five fetched the page directly from the origin.
Who didn't announce themselves
- Gemini: Zero requests from any Google user-agent during prompt window. Answered entirely from its own index without performing a live provider-side fetch.
- Copilot: Plain Chrome 135 on Linux x86_64, full browser-style Accept. Fetched but indistinguishable from human visitors.
- Grok: Plain Mac Safari 26 and plain Mac Chrome 143. Fetched but indistinguishable from human visitors.
Key behavioral patterns observed
ChatGPT: Hits from multiple source IPs within the same burst, typically pulling several candidate pages at once while deciding which to cite. In a 24-hour production window, ChatGPT-User requests came from five distinct Azure ranges: 23.98.x.x, 20.215.x.x, 40.67.x.x, 51.8.x.x, and 51.107.x.x.
Claude: Always fetches /robots.txt before every page fetch, from Anthropic-owned IP space in the 216.73.216.0/24 range. Follows redirects cleanly, including trailing-slash normalization. Anthropic runs three distinct bots: Claude-User (user-initiated retrieval), Claude-SearchBot (search index), and ClaudeBot (training crawler).
Perplexity: Direct fetch with no Accept header or referrer. PerplexityBot (their search-indexing crawler) separately pinged /robots.txt. The author notes Perplexity can retrieve live but doesn't have to, as it can answer from its own index.
Gemini: No live provider-side fetch observed. Google doesn't publish a retrieval-specific user-agent for Gemini, and according to Google's crawler documentation, AI Overviews and AI Mode ground on the same Search index that Googlebot populates.
The experiment distinguishes between two signals: provider-side fetch (assistant hits origin with dedicated user-agent) and real clickthrough visits (human reads AI answer and clicks citation, arriving as normal browser with assistant as referrer). Combining both into a single "AI-traffic" number hides this useful distinction.
📖 Read the full source: HN AI Agents
👀 See Also

Ory Lumen: Open Source Local Semantic Search Plugin for Claude Code
Ory Lumen is a Claude Code plugin that indexes codebases using Ollama with a code embedding model and SQLite-vec for semantic search, addressing Claude Code's performance issues with large codebases. The tool is free, local-only, and includes a SWE-style benchmark test harness for reproducible results.

Running OpenClaw and Codex CLI Natively on Android via AnyClaw APK
A developer has packaged OpenClaw and Codex CLI into an Android APK called AnyClaw, enabling the gateway and Control UI to run locally on ARM64 Android 7.0+ devices without root. The project required building dependencies from source and patching multiple components to handle Android-specific constraints.

DESIGN.md: A format spec for describing visual identity to coding agents
DESIGN.md combines YAML design tokens with markdown prose to give AI coding agents a persistent, structured understanding of a design system. Includes a linter and diff tool.

Qwen 3.6 27B hits 2.5x speed with MTP speculative decoding on llama.cpp
A Reddit user reports 2.5x faster inference on Qwen 3.6 27B using MTP speculative decoding with a custom llama.cpp PR, achieving 28 tok/s on Mac M2 Max 96GB. Includes pre-converted GGUF quants and fixed chat templates.