"""search — semantic search across the user's notes and tasks.

Mirrors the existing fable-mcp contract so Claude's prior usage pattern keeps
working. Differences from fable-mcp:
  - calls services.embeddings.semantic_search_notes directly instead of HTTP
  - user_id comes from mcp.current_user_id() rather than a global API key
"""
from __future__ import annotations

import time

from scribe.mcp._context import current_user_id
from scribe.services.access import owner_names_for
from scribe.services.embeddings import DEFAULT_SIMILARITY_THRESHOLD, semantic_search_notes
from scribe.services.retrieval_telemetry import record_retrieval


async def search(
    q: str,
    content_type: str = "all",
    limit: int = 10,
    project_id: int = 0,
    system_id: int = 0,
) -> dict:
    """Semantic search over the user's existing notes and tasks — Scribe's recall.

    Reach for this BEFORE answering a question about the user's work or starting
    a task: the user's second-brain almost always already holds related prior
    art. Check for an existing ticket before opening a new one (search with
    content_type='task'), and for prior notes/decisions before re-deriving them.
    Treating Scribe as the first place to look — not a place to only write — is
    the difference between it being a trustworthy record and a write-only log.

    Args:
        q: search query string.
        content_type: 'all' (default), 'note' (notes only), or 'task' (tasks only).
        limit: maximum number of results (1-50).
        project_id: Scope results to one project. PASS THE ACTIVE PROJECT'S ID
            whenever a project is in scope (the one you entered with
            enter_project) — otherwise this searches across ALL projects and
            bleeds unrelated work into the result set. 0 = search everything
            (use only when you genuinely want a cross-project sweep).
        system_id: Narrow to records tagged to one System (a named
            subsystem/area — enter_project lists them). Use when investigating
            a specific subsystem: it cuts the candidates to records someone
            deliberately filed under that area. 0 = no system filter.
            list_system_records gives the same slice unranked.

    Returns:
        {"results": [{"id", "title", "body", "is_task", "tags", "similarity"}],
         "total": int}

    A result marked `shared: true` with an `owner` belongs to another user —
    that person's suggestion, not the operator's own record or settled practice.
    Weigh it on its merits and say whose it is when you use it.
    """
    uid = current_user_id()
    limit = max(1, min(limit, 50))
    is_task = {"note": False, "task": True}.get(content_type)  # None => any
    t0 = time.perf_counter()
    raw = await semantic_search_notes(
        uid, q, limit=limit, is_task=is_task,
        project_id=project_id or None,
        system_id=system_id or None,
        # An explicit search reaches everything the operator may read, including
        # records shared with them one-to-one.
        scope="read",
    )
    record_retrieval(
        user_id=uid, source="mcp_search", query=q,
        threshold=DEFAULT_SIMILARITY_THRESHOLD, limit=limit,
        project_id=project_id or None, is_task=is_task, results=raw,
        duration_ms=(time.perf_counter() - t0) * 1000.0,
    )
    owners = await owner_names_for(
        {int(note.user_id) for _s, note in raw if note.user_id != uid}
    )
    return {
        "results": [
            {
                "id": note.id,
                "title": note.title,
                "body": (note.body or "")[:240],
                "is_task": bool(note.is_task),
                "tags": list(note.tags or []),
                "similarity": float(score),
                **(
                    {"shared": True, "owner": owners.get(int(note.user_id))}
                    if note.user_id != uid else {}
                ),
            }
            for score, note in raw
        ],
        "total": len(raw),
    }


def register(mcp) -> None:
    mcp.tool(name="search")(search)
