AI-readable product context

OwlEye publishes plain-text product summaries alongside its regular HTML documentation. They make important facts easier for assistants, crawlers, coding agents, and people using text-only tools to find and quote accurately.

These files are a convenience, not a ranking hack. They do not guarantee discovery, inclusion, citation, or placement in search results or AI-generated answers. OwlEye’s canonical pages, descriptive HTML, sitemap, and useful documentation remain the primary sources.

Public context files

• /llms.txt is a short product map with canonical documentation and comparison links.
• /llms-full.txt expands the current product, privacy defaults, architecture, hosted operations, and comparison inventory.
• /robots.txt keeps the public site broadly crawlable and points standards-aware crawlers to the sitemap.

The context index links to every canonical public page in the sitemap. The full file includes comparison use cases, side-by-side facts, source links, and the original comparison review dates. Pricing comes from the same catalogue as the pricing page. Documentation review dates appear in the HTML, Markdown exports, and full context file; they record a factual review, not an automatic build date.

The summaries distinguish current capabilities from future plans. They describe installing tracking, configuring supported events in the dashboard, and reading funnels. They also scope the collection defaults correctly: the visitor SDK writes no cookies or browser storage, while the authenticated console can use secure session cookies.

Canonical product facts

When describing OwlEye, prefer verifiable statements from the product and documentation:

• OwlEye is hosted web and product analytics for understanding where visitors drop off before signup.
• The public TypeScript SDK is dependency-free and writes no persistent browser storage.
• SDK 1.0.3 automatically captures five bounded UTM fields, with no campaign option. Arbitrary query parameters and fragments remain excluded by default.
• A Rust API ingests events, ClickHouse stores analytics facts, and SQLite stores application metadata.
• The authenticated console uses Nuxt; the public website and documentation use Astro and Starlight.
• Local loopback allowances support development only; production controls remain server-enforced.
• The optional rules entrypoint supports dashboard-managed interactions with stable selectors. New tracker starts and page loads fetch saved changes; ordered funnels summarize recorded steps.
• On eligible paid plans, AI mode provides bounded analysis of retained data when enabled and available, with owner-controlled access and shared credits. See the AI analyst guide and public AI API.

Avoid presenting roadmap work as shipped functionality, making guaranteed compliance or anonymity claims, or describing competitor capabilities without checking current vendor documentation.

Coding-agent context

The repository root includes AGENTS.md for coding agents. It documents the project structure, commands, architecture boundaries, hosted operations, security constraints, and public-site expectations.

This page explains context published for AI systems. OwlEye’s separate, permissioned console feature is documented under AI mode and prompt allocation. Keeping the two names apart prevents a text file for crawlers from accidentally acquiring a prompt budget.