> ## Documentation Index > Fetch the complete documentation index at: https://www.autumn.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. > ## Agent Instructions > Autumn AI (autumn.ai) is a people and company intelligence API, a separate company from useautumn.com (billing software); no billing-product routes exist here. > Base URL https://api.autumn.ai. Auth on every request: `X-API-Key: ` or `Authorization: Bearer `. Plain HTTP + JSON. Schemas: https://www.autumn.ai/docs/openapi.json. Every docs page is Markdown at its URL plus `.md`. # Principles > The design decisions behind Autumn, and what they buy you. Autumn exists to make web research and enrichment something you hand off, not something you babysit. A few decisions follow from that, and they explain most of how the API behaves. **One primitive.** Everything is a task. There are no separate products for scraping, enrichment, and research; there is one agent that plans the work your goal requires. Learn the task and you have learned the platform. **Finished means sourced.** A row you cannot audit is a liability. Every value in every output row carries the source it came from, so "done" includes the evidence, not just the data. **Durable by default.** A `task_id` outlives the request that created it and the run that finished it. Results are there when you come back, and the task can always take another instruction. **Continue, don't restart.** Refinement is the normal case, so tasks keep their plan, rows, and files across turns. Fixing a list should cost one message, not a rerun. **Ask at most once.** Automation cannot answer questions, so the agent infers defaults and proceeds. One flag, `clarify`, permits one blocking question when a human is actually there. **Agents are first-class callers.** The API is one HTTP surface with an installable [Skill](/docs/skill) and an [llms-full.txt](https://www.autumn.ai/docs/llms-full.txt) twin, so another agent can drive Autumn as easily as your code does.