Use this when the user (especially a researcher or a research agent) asks for
peer-reviewed findings: "latest evidence on X", "highly-cited papers about Y",
"what does the literature say about Z". This is NOT a memory tool — it does not
read the user's private memory, and it needs no per-user API key, so it works
even when Awareness memory is not configured (the MCP connection itself still
needs its own token).

Coverage: condensed-matter, quantum-information, materials, machine-learning,
renewable-energy, chemistry, biology, medicine, neuroscience, computer-science
(2022-2026, cited >= 50), plus a business supply/demand domain.

What comes back (anonymous preview mode):
  title, snippet (preview), confidence, source_ref (DOI), citation_count,
  domain/topic, and a detail page URL. Full content is NOT in the preview —
  tell the user it is paid retrieval via POST /api/v1/public/retrieve with an
  API key (see https://awareness.market/en/knowledge for the KaaS product).

Args:
    query: Natural-language research question or keywords (2-1000 chars).
    domain: "science" (default) or "business".
    topic: Optional sub-topic slug, e.g. "medicine", "condensed-matter",
        "supply-chain". Empty = search all topics in the domain.
    top_k: Max results, 1-20 (default 5; anonymous callers are capped at 3).
    include_graph: When true, also return same-topic related items.

Returns:
    {"results": [{id, title, snippet, confidence, source_ref, citation_count,
    domain, topic, url}], "related": [...], "total": int, "mode": str}
    `mode` is "preview" (anonymous) or "full" (authenticated).