Spinach AI

Fetch full content of a specific meeting by its ID (e.g. "meeting:abc123"). Use after `list_meetings` once you have identified a relevant meeting ID. To fetch multiple meetings at once, use `fetch`. Use the optional `include` array to request only the sections you need: "summary" (full meeting summary text), "action_items" (complete action item list with owners), "decisions" (all key decisions), "chapters" (chapter titles + detailed summaries), "participants" (names + emails where available), "transcript" (raw transcript — large; use with `chapter_index` to scope to one chapter), "metadata" (platform, duration, series ID, org domain), "collections" (recording collections this meeting belongs to — id + name). Omitting `include` returns all sections except the transcript. To fetch a transcript for a specific chapter, pass `include: ["transcript"]` and `chapter_index` (0-based index into the chapters array).

Live transcript of an in-progress meeting. Use `get` for ended meetings. No `id`: returns the transcript when one meeting is active, or JSON `{active_meetings[{id,title,platform,started_at,last_line}]}` when multiple are active. With `id` (meeting/bot id): returns that meeting's transcript as `Speaker: words` lines prefixed by a header (Meeting ID, Title, Platform, Started at). Requires live captions enabled. Only reliable in English.

List recording collections the user has access to. Returns per collection: id, name, recording_count, role (owner | collaborator | viewer), created_at. Use the returned collection `id` with `list_meetings` (pass as `collection_id`) to filter meetings within a specific collection. Collections are curated groups of meetings organized by the user or shared with them. Only collections the user has at least viewer access to are returned.

Step 1 of 2: list and filter meetings with lightweight metadata. Returns per meeting: id, title, date, participants (names), platform, is_external, has_transcript, url, tldr, summary_snippet (≤600 chars: top action items/decisions/agenda), chapters ({title, summary, subsections[]} per chapter), action_item_count, decision_count. Does NOT return: full summary, full action/decision lists, or transcript. Use `get` or `fetch` once you have relevant IDs. ## Search strategies (chapter text is NOT indexed) **1 — Title (instant):** `title_query` when the topic is likely the meeting's main subject. **2 — Chapter scan:** Request `fields:["id","title","date","chapters"]`, scan `chapters[].summary` across results, then fetch matches. **3 — Narrow first:** Combine `from_date`/`to_date`, `participant`, `platform`, or `recurring_meeting_series_id` to shrink the set. Use `limit:100`. **4 — Collection:** Use `collection_id` from `list_collections` to scope to a curated group of meetings. **5 — Code-filter:** Paginate and filter `chapters[].summary` programmatically before fetching. If a result looks relevant, call `get` with its ID to retrieve full content before answering. Use `fields` to return only what you need (reduces tokens; `id` always included). Paginate via `next_cursor` → `cursor`.

Hybrid BM25 + semantic search across indexed meeting chapters and subsections. Returns meetings ranked by Reciprocal Rank Fusion (RRF) of keyword and semantic signals. Each result includes: • `id` — use with `get` to fetch the full meeting • `score` — RRF relevance (keyword + semantic combined) • `title`, `date`, `url` • `matched_chapters` — up to 3 chapters/subsections that drove the match Pass `include: ["transcript"]` to add verbatim transcript text to each matched chapter. ## vector_weight (0.0–1.0, default 0.5) Balances semantic (vector) vs. keyword (BM25) scoring in RRF fusion: • 0.5 — balanced hybrid; best default for most queries • 0.7–1.0 — prefer semantic; use for intent/concept queries where the user expresses meaning rather than exact words: "meetings where the team seemed frustrated", "discussions about technical direction", "when did we talk about burnout" • 0.1–0.3 — prefer keyword; use when the query contains specific names, IDs, ticket numbers, or exact quoted phrases: "SAI-3364", "Kirill's comment about the deadline", "bun.lock conflict", "unfunny remarks" • 0.0 — keyword only (BM25); 1.0 — semantic only (vector) Metadata filters (`from_date`, `to_date`, `platform`, `is_external`) narrow the candidate set. Max 100 results (default 25). No cursor — ranked by relevance, not date. For full content, call `get` with a returned `id`.