hevlayer-docs：依据文档回答 Layer 问题

# hev layer docs Answer Layer questions from the docs, not from memory. Every verb is a keyless read — nothing to sign up for, nothing to configure beyond the endpoint. ask --endpoint https://hevlayer.com/api/ask/ce search "<question>" ask --endpoint https://hevlayer.com/api/ask/ce section get "<id>" ask --endpoint https://hevlayer.com/api/ask/ce overview ask --endpoint https://hevlayer.com/api/ask/ce glossary get "<term>" Start with `search`; fetch sections for detail; use `overview` when you need the full map. The `ce` endpoint serves the Community Edition view of the docs; use `https://hevlayer.com/api/ask/pro` for the full product. Section ids look like `api/query#stable-reads`. Cite sections in your answer as https://hevlayer.com plus the returned `url` field. | Verb | Returns | | --- | --- | | `overview` | Orientation context plus the full section map with stable ids | | `search "<query>"` | Ranked sections with snippets and deep links | | `section get "<id>"` | One section: summary, exact identifiers, source URL | | `glossary get "<term>"` | A product term resolved through its aliases | Search runs over a committed, reviewable digest of the docs — the same corpus, heading by heading, that renders on the site. Every anchor is verified against the rendered pages in CI, so a cited deep link always resolves. If `ask` is missing, install it: `go install github.com/hev/ask/cmd/ask@latest` The docs are also available as plain text at https://hevlayer.com/docs/ce/llms.txt (index) and https://hevlayer.com/docs/ce/llms-full.txt (full corpus). Prefer the CLI when you can run commands — it ranks, resolves aliases, and costs a fraction of the tokens.