llms.txt — AI-friendly documentation
A single URL exposes the entire outsend documentation to any AI assistant — no auth, no scraping, no parsing.
The outsend documentation is published in the llms.txt format. Any AI assistant — Claude, ChatGPT, Cursor, Perplexity, or a local model — can ingest the full reference in one fetch.
The two endpoints
| URL | Purpose |
|---|---|
/docs/llms.txt |
Flat index — one line per page, with title + URL + one-line summary |
/docs/llms-full.txt |
Full bundle — every page concatenated, delimited by <!-- doc: <slug> --> |
Both endpoints return text/plain with no auth, no rate limit, no JS rendering required.
Use it from an AI assistant
Most AI clients now detect llms.txt automatically when a domain is mentioned. For the ones that don't, paste the URL directly:
https://outsend.xyz/docs/llms-full.txt
The bundle is ~150 KB and fits comfortably in any modern context window.
Per-section bundles
For narrower scopes, the per-section endpoints are also available:
| URL | Contains |
|---|---|
/docs/_bundle/concepts.txt |
Only the Concepts pages |
/docs/_bundle/modules.txt |
Only the Modules pages |
/docs/_bundle/api.txt |
Only the API reference |
/docs/_bundle/integration.txt |
Only the Integration pages |
The Copy button
Every page in this documentation has a Copy button in the top-right corner. It exposes the same bundles, but as a one-click clipboard action:
- Copy this page (raw markdown)
- Copy this section
- Copy entire docs
The "Copy entire docs" action is the recommended path when handing the docs to an AI assistant interactively.
Why this matters
AI assistants are increasingly used as the integration layer between SaaS products. A documentation that an assistant can ingest cleanly — without scraping, login flows, or HTML parsing — is integratable; one that cannot, is not.
outsend's docs are designed to be readable by humans, but their first audience is the LLM that will draft the integration code, write the prompt template, or diagnose the misconfigured pipeline.
What's next
- API overview — the surface the assistant will call
- MCP — the protocol the assistant should prefer