feat: force a seller scan over active conversations from the inbox

Adds a "Scan for sellers" button to the conversations header, backed by
POST /api/conversations/seller-scan.

The sweep reuses the existing seller detection rather than inventing a
second one: the configured keyword/domain list, the seller-link funnel
patterns, and the aiReplyScreening confidences all decide the verdict, so
a swept conversation lands in the state the live reply loop would have
given it. Being operator-forced, it deliberately ignores filterSellers
and aiReplyScreening.enabled.

AI is the last resort. Conversations are skipped when already flagged or
killed, settled for free by the deterministic rules, or skipped against a
durable sellerScreenedKey watermark when nothing new has arrived since
the last clean sweep. Only the remainder reaches the model, batched eight
at a time through a new screenConversationsForSellers, so the system
prompt and round trip are paid per batch instead of per conversation. A
classifier outage degrades the sweep instead of failing it.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

tests/openrouter-client.test.ts

@@ -85,6 +85,56 @@ describe('OpenRouterClient', () => {
     });
   });
 
+  describe('screenConversationsForSellers', () => {
+    const batch = [
+      { id: '1', username: 'alice', messages: [{ sender: 'alice', text: 'my menu is on my page', isSelf: false }] },
+      { id: '2', username: 'bea', messages: [{ sender: 'bea', text: 'what are you up to today?', isSelf: false }] },
+    ];
+
+    it('classifies a whole batch in one request and keys verdicts back by id', async () => {
+      mockCreate.mockResolvedValueOnce({
+        model: 'chat-model',
+        choices: [{ message: { content: '{"results":[{"id":"1","seller":true,"confidence":0.93,"evidence":"a menu"},{"id":"2","seller":false,"confidence":0.05,"evidence":"small talk"}]}' } }],
+        usage: {},
+      });
+
+      await expect(client.screenConversationsForSellers(batch)).resolves.toEqual([
+        { id: '1', seller: true, confidence: 0.93, evidence: 'a menu' },
+        { id: '2', seller: false, confidence: 0.05, evidence: 'small talk' },
+      ]);
+      expect(mockCreate).toHaveBeenCalledTimes(1);
+      const request = mockCreate.mock.calls[0][0];
+      expect(request.temperature).toBe(0);
+      expect(request.messages[1].content).toContain('CONVERSATION id=1');
+      expect(request.messages[1].content).toContain('BEGIN UNTRUSTED CONVERSATION DATA');
+    });
+
+    it('drops verdicts for ids it never asked about', async () => {
+      mockCreate.mockResolvedValueOnce({
+        model: 'chat-model',
+        choices: [{ message: { content: '{"results":[{"id":"9","seller":true,"confidence":0.99,"evidence":"invented"}]}' } }],
+        usage: {},
+      });
+
+      await expect(client.screenConversationsForSellers(batch)).resolves.toEqual([]);
+    });
+
+    it('makes no request at all for an empty batch', async () => {
+      await expect(client.screenConversationsForSellers([])).resolves.toEqual([]);
+      expect(mockCreate).not.toHaveBeenCalled();
+    });
+
+    it('throws when no model returns usable JSON', async () => {
+      mockCreate.mockResolvedValue({
+        model: 'chat-model',
+        choices: [{ message: { content: 'they all look like sellers to me' } }],
+        usage: {},
+      });
+
+      await expect(client.screenConversationsForSellers(batch)).rejects.toThrow('no JSON object');
+    });
+  });
+
   describe('isRefusal (internal)', () => {
     // We test refusal detection by checking the analyzeImage behavior
     // since isRefusal is private. We do this by mocking responses that