Fix combat advisor "AI unavailable (parse)" — coerce numeric counts

The encounter-balance schema was the only AI schema with a numeric field.
LLMs routinely emit numbers as JSON strings ("count": "2"), which z.number()
rejects, failing the whole safeParse and falling back to deterministic with a
"parse" error. The all-string NPC/session/quest schemas never hit this.

- Coerce monster counts (z.coerce.number) and widen the upper bound 8->12 so a
  string or slightly over-eager count is accepted, not rejected. min(1) stays.
- Tell the model in the prompt that count is a plain integer and reasoning /
  targetDifficulty are required.
- Surface the real failure message in the advisor instead of the opaque kind.
- Add a regression test that string counts coerce to numbers.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

src/features/assistant/useEncounterAdvisor.ts

@@ -137,7 +137,7 @@ export function useEncounterAdvisor(campaign: Campaign, encounter: Encounter) {
             return;
           }
         } else if (!res.ok) {
-          setMessage(`AI unavailable (${res.error}); showing a deterministic pick.`);
+          setMessage(`AI unavailable: ${res.message} Showing a deterministic pick.`);
         }
       }
 

src/lib/assistant/prompts.test.ts

@@ -44,4 +44,9 @@ describe('balanceSuggestionSchema', () => {
     expect(balanceSuggestionSchema.safeParse({ reasoning: 'x', add: [{ name: 'Ogre', count: 0 }], targetDifficulty: 'Medium' }).success).toBe(false);
     expect(balanceSuggestionSchema.safeParse({ add: [], targetDifficulty: 'Medium' }).success).toBe(false);
   });
+  it('coerces string counts (a common model quirk) instead of rejecting', () => {
+    const r = balanceSuggestionSchema.safeParse({ reasoning: 'x', add: [{ name: 'Ogre', count: '2' }], targetDifficulty: 'Medium' });
+    expect(r.success).toBe(true);
+    if (r.success) expect(r.data.add[0]!.count).toBe(2);
+  });
 });

src/lib/assistant/prompts.ts

@@ -2,17 +2,22 @@ import { z } from 'zod';
 import type { Character } from '@/lib/schemas';
 import type { CampaignContext, CreatureCandidate } from './context';
 
+// Counts are coerced (models routinely return numbers as JSON strings, e.g. "2")
+// and allow a wider upper bound than the prompt asks for, so a slightly
+// over-eager suggestion is accepted rather than rejecting the whole response.
+const monsterCount = z.coerce.number().int().min(1).max(12);
+
 export const balanceSuggestionSchema = z.object({
   reasoning: z.string(),
   add: z.array(z.object({
     name: z.string(),
-    count: z.number().int().min(1).max(8),
+    count: monsterCount,
     ref: z.string().optional(),
   })),
   /** Monsters to take out when the fight is over-tuned (already at/above target). */
   remove: z.array(z.object({
     name: z.string(),
-    count: z.number().int().min(1).max(8),
+    count: monsterCount,
   })).optional(),
   targetDifficulty: z.string(),
 });
@@ -35,7 +40,8 @@ export function buildBalancePrompt(
     `You are an encounter-balancing assistant for a ${ctx.systemLabel} game master. ` +
     `Recommend which creatures to ADD to the current encounter to bring it to roughly "${current.targetDifficulty}" difficulty. ` +
     `You MUST choose only from the provided candidate creatures (by exact name). Do not invent creatures or use any from another system. ` +
-    `Prefer 1–3 distinct creatures with sensible counts. Keep the reasoning to one or two sentences.`;
+    `Prefer 1–3 distinct creatures with sensible counts. Keep the reasoning to one or two sentences. ` +
+    `Each "count" must be a plain integer (e.g. 2, not "2"). Always include "reasoning" and "targetDifficulty".`;
 
   const candidateList = current.candidates
     .map((c) => `- ${c.name} (rating ${c.rating}${c.hp ? `, hp ${c.hp}` : ''}${c.ac ? `, ac ${c.ac}` : ''})`)