handleThreadsList lists all threads (.from("threads")...order(...)) without filtering by user_id. You’re relying on RLS to prevent cross-user reads, but that means:

• the endpoint’s behavior becomes tightly coupled to RLS being enabled and correct in every environment (including local/dev)
• failures/misconfigurations become data leaks
• queries can become more expensive than necessary because Postgres must apply policy filters

Given the stated goal of per-user thread isolation, you should also filter at the query level.

const { data, error } = await supabase
  .from("threads")
  .select("id, created_at, updated_at, name, metadata")
  .eq("user_id", userId)
  .order("updated_at", { ascending: false });

handleThreadUpdate updates by id only. With RLS enabled it will likely be blocked for non-owners, but you should not depend on that as the only isolation boundary for an app-level API.

Also, as written, it updates the row even if the threadId doesn’t exist (no error), then re-reads and returns 404. That’s fine, but adding the user_id filter makes the update and read consistent and avoids revealing whether a thread exists for other users.

const { error } = await supabase
  .from("threads")
  .update(update)
  .eq("id", threadId)
  .eq("user_id", userId);

// ... later
const { data: thread, error: readError } = await supabase
  .from("threads")
  .select("id, created_at, updated_at, name, metadata")
  .eq("id", threadId)
  .eq("user_id", userId)
  .maybeSingle();

In handleAdvanceStream, you load historyRows before inserting messageToAppend, then send initialMessages (derived from historyRows) along with messageToAppend to Tambo. This seems intentional (history excludes the new message), but you also persist messageToAppend to DB first.

If the downstream Tambo call fails (network, auth, 5xx), you’ve already written the user message, but you return an error and never persist assistant/tool responses. This creates “dangling” user messages and can confuse clients on retry (duplicate user message, different assistant response, etc.).

The SSE parser uses rawLine = buffer.slice(0, nl).trim(). Trimming is risky for SSE:

• it can remove meaningful leading spaces in data: payloads (rare but valid)
• it can change empty data: lines semantics
• it can also collapse lines that should be forwarded as-is

Additionally, SSE events can have multiple data: lines per event; this implementation treats each line independently and will silently drop/mangle multi-line events.

const rawLine = buffer.slice(0, nl);

persistMessages does upsert(rows) with no conflict target or dedupe logic shown. If the table has a PK on id (it does), that’s fine, but you’re mapping Tambo dto.id to random UUIDs and persisting those.

However, you also insert messageToAppend with a random UUID earlier. If Tambo also echoes the appended user message back as a response DTO, you may end up with two persisted copies of the same logical message (one from the initial insert, one from the streamed final upsert), since the IDs differ.

SSE correctness: outgoing stream missing blank line delimiter

Server-Sent Events require events to be terminated by a blank line (\n\n). This implementation enqueues data: ...\n and data: DONE\n but not the required extra newline. Some clients will buffer indefinitely or parse incorrectly.

Related: the error path enqueues error: ...\n which is not a standard SSE field (clients typically listen for event: + data:). If the Tambo client expects this custom error: prefix, fine—but the missing \n\n is still a protocol issue.

const outLine = `data: ${JSON.stringify(chunk)}\n\n`;
controller.enqueue(encoder.encode(outLine));

controller.enqueue(encoder.encode("data: DONE\n\n"));

Persisting threads.updated_at should not bypass DB authority

persistMessages() updates threads.updated_at by sending an explicit ISO string:

.update({ updated_at: new Date().toISOString() })

But the migration already adds a trigger (threads_set_updated_at) to set updated_at = now() on update. Setting the value from the app defeats that purpose and risks clock skew.

You can update a no-op field (or re-set name to itself) or update updated_at using a DB function (if you prefer), but best is to let the trigger handle the timestamp.

const { error: threadUpdateError } = await supabase
  .from("threads")
  .update({})
  .eq("id", persistentThreadId);

Proxy security: forwarding cookie/authorization headers to Tambo

proxyToTambo() clones all incoming headers and adds x-api-key. That likely forwards cookie and possibly authorization to the upstream Tambo API. This is an unnecessary data leak (session cookies, CSRF tokens, etc.) to a third-party service.

Given this is an authenticated proxy, you should explicitly allowlist headers instead of pass-through, or at least strip sensitive ones (cookie, authorization, x-forwarded-* as needed).

const headers = new Headers();
headers.set("x-api-key", apiKey);
headers.set("accept", request.headers.get("accept") ?? "application/json");
headers.set("content-type", request.headers.get("content-type") ?? "application/json");

headers.delete("cookie");
headers.delete("authorization");

message-suggestions.tsx removes useTamboSuggestions and hard-codes isGenerating=false, error=null, and returns [] suggestions once the thread has messages.

That effectively disables generated suggestions entirely after the first message. If that’s intended as a temporary workaround, it should be explicit; otherwise it’s a functional regression (UI will show nothing where it previously generated suggestions).

The migration includes destructive "one-time legacy cleanup":

delete from public.threads where user_id is null;
delete from public.messages where thread_id not in (select id from public.threads);

This is dangerous in real deployments:

• it irreversibly deletes data on migration apply
• it can delete data unexpectedly if the schema is applied to an environment with partially migrated/seeded data
• threads.user_id is not null in this same migration, so user_id is null should never be true for newly created rows; this cleanup is either obsolete or indicates pre-existing inconsistent schema/data.

Destructive data cleanup should be a separate, explicitly run script (or at least guarded behind checks).

-- only in non-production, if you have a reliable marker
DO $$
BEGIN
  IF current_setting('app.env', true) = 'development' THEN
    DELETE ...;
  END IF;
END $$;