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Step 4 of #278, product half. The audit that motivated it: one System in project 2, thirty records tagged, nothing since July 28 — three days after the feature landed. Not a discipline failure; retrieval was completely blind to the association (zero references in embeddings, knowledge, search, auto-inject, or enter_project), so tagging was a write-side label with no read-side payoff, and labels nobody reads don't get maintained. Three changes, ordered by what makes the others workable: 1. enter_project returns the project's Systems (id, name, first line of the charter). Load-bearing for the tagging instruction: you cannot ask an agent to check a record against a vocabulary it never sees. Trimmed because it rides on every session start; the full charter stays get_system's job. Present-and-empty rather than absent when a project has none — "no named areas yet" is information the create-the-System instruction acts on. 2. search accepts system_id, MCP and REST (#33). Implemented once in semantic_search_notes as an EXISTS against record_systems — an association filter deciding candidate-set membership before scoring, like project_id, not a ranking signal. The REST route's missing project filter stays #2463's: it carries a default-scope UI decision this change must not preempt. 3. The instructions (#119, _INSTRUCTIONS + using-scribe skill; plugin 0.1.25 for the cache): - Tag as you write, with an executable test — "would someone investigating that subsystem want this in the pile list_system_records returns?" — rather than "tag appropriately", which is what died. - Create the System when the area has no record: the two-or-more test snippets use, plus "don't wait to be asked to name an area that plainly exists", because the agent's default was leaving un-modelled areas un-modelled forever. - State vs chronicle: dev-logs are written once and never rewritten; durable findings live in the System's reference note, updated in place — safe because note versions are the changelog, which has existed since the feature shipped and was never named as one. list_system_records' docstring now sells it as the way to READ a subsystem, reference note first. No auto-inject boost by System — vocabulary and filter first, measure before adding ranking behaviour (the #2486 lesson). Refs #278, #2546
100 lines
4.0 KiB
Python
100 lines
4.0 KiB
Python
"""search — semantic search across the user's notes and tasks.
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Mirrors the existing fable-mcp contract so Claude's prior usage pattern keeps
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working. Differences from fable-mcp:
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- calls services.embeddings.semantic_search_notes directly instead of HTTP
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- user_id comes from mcp.current_user_id() rather than a global API key
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"""
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from __future__ import annotations
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import time
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from scribe.mcp._context import current_user_id
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from scribe.services.access import owner_names_for
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from scribe.services.embeddings import DEFAULT_SIMILARITY_THRESHOLD, semantic_search_notes
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from scribe.services.retrieval_telemetry import record_retrieval
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async def search(
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q: str,
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content_type: str = "all",
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limit: int = 10,
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project_id: int = 0,
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system_id: int = 0,
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) -> dict:
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"""Semantic search over the user's existing notes and tasks — Scribe's recall.
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Reach for this BEFORE answering a question about the user's work or starting
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a task: the user's second-brain almost always already holds related prior
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art. Check for an existing ticket before opening a new one (search with
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content_type='task'), and for prior notes/decisions before re-deriving them.
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Treating Scribe as the first place to look — not a place to only write — is
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the difference between it being a trustworthy record and a write-only log.
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Args:
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q: search query string.
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content_type: 'all' (default), 'note' (notes only), or 'task' (tasks only).
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limit: maximum number of results (1-50).
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project_id: Scope results to one project. PASS THE ACTIVE PROJECT'S ID
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whenever a project is in scope (the one you entered with
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enter_project) — otherwise this searches across ALL projects and
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bleeds unrelated work into the result set. 0 = search everything
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(use only when you genuinely want a cross-project sweep).
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system_id: Narrow to records tagged to one System (a named
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subsystem/area — enter_project lists them). Use when investigating
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a specific subsystem: it cuts the candidates to records someone
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deliberately filed under that area. 0 = no system filter.
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list_system_records gives the same slice unranked.
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Returns:
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{"results": [{"id", "title", "body", "is_task", "tags", "similarity"}],
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"total": int}
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A result marked `shared: true` with an `owner` belongs to another user —
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that person's suggestion, not the operator's own record or settled practice.
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Weigh it on its merits and say whose it is when you use it.
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"""
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uid = current_user_id()
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limit = max(1, min(limit, 50))
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is_task = {"note": False, "task": True}.get(content_type) # None => any
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t0 = time.perf_counter()
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raw = await semantic_search_notes(
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uid, q, limit=limit, is_task=is_task,
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project_id=project_id or None,
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system_id=system_id or None,
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# An explicit search reaches everything the operator may read, including
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# records shared with them one-to-one.
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scope="read",
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)
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record_retrieval(
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user_id=uid, source="mcp_search", query=q,
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threshold=DEFAULT_SIMILARITY_THRESHOLD, limit=limit,
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project_id=project_id or None, is_task=is_task, results=raw,
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duration_ms=(time.perf_counter() - t0) * 1000.0,
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)
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owners = await owner_names_for(
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{int(note.user_id) for _s, note in raw if note.user_id != uid}
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)
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return {
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"results": [
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{
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"id": note.id,
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"title": note.title,
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"body": (note.body or "")[:240],
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"is_task": bool(note.is_task),
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"tags": list(note.tags or []),
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"similarity": float(score),
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**(
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{"shared": True, "owner": owners.get(int(note.user_id))}
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if note.user_id != uid else {}
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),
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}
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for score, note in raw
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],
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"total": len(raw),
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}
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def register(mcp) -> None:
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mcp.tool(name="search")(search)
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