HitKeep llms.txt
Browse HitKeep documentation as markdown. Click any page in the sidebar to view it, or copy the full llms.txt for your AI tools.
What is HitKeep's llms.txt?
HitKeep publishes an /llms.txt file that provides AI systems with a structured index of its documentation. It follows the llms.txt specification, organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what HitKeep offers and where to find details.
Sections: Key Documentation · Comparison Pages · REST API · Release Tracking · Blog · Cloud · and 4 more
Add HitKeep Docs to Your AI Assistant
Select your tool to see how to add HitKeep's llms.txt as a documentation source.
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Open any chat or composer panel
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Type @Docs and select "Add new doc"
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Paste the URL: https://hitkeep.com/llms.txt
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Wait for the green dot (indexing complete)
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Reference @Docs in chat when asking about HitKeep
Cursor crawls the URL and indexes all subpages. Add a trailing slash to index child pages too.
Frequently Asked Questions
HitKeep publishes its llms.txt at https://hitkeep.com/llms.txt. This file provides a structured, markdown-formatted index of HitKeep's documentation that AI systems can consume to understand the project's APIs, guides, and references.
Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of HitKeep's documentation so it can provide better code suggestions and answers about HitKeep.
HitKeep's llms.txt contains 10 sections and 65 documentation links in 8.6 KB (~2.2k tokens). Key sections include Key Documentation, Comparison Pages, REST API, Release Tracking, Blog, Cloud.
The concise llms.txt index is approximately 2.2k tokens (8.6 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline.
HitKeep is a privacy-first web analytics platform built on the principle that your data belongs to you. You can self-host it as a single Go binary with zero external service dependencies, or run it in HitKeep Cloud in EU or US regions. Data lives in DuckDB and can be exported at any time in open formats (JSON, CSV, Parquet). Current Linux release binaries target a modern glibc baseline (`glibc 2.34+`).. HitKeep's llms.txt file helps AI systems understand this by providing a structured overview of its documentation, making it easier for developers to get accurate AI-assisted help when working with HitKeep.
Yes. Use the free llms.txt generator at mdream.dev/tools/llms-txt/generator to crawl your site and produce a spec-compliant llms.txt file. You can also validate existing files with the llms.txt validator.