fix: correct OpenCode cache hit rates

Include cache reads and writes in the complete input denominator for OpenCode usage. Use the same calculation for stored records, summary totals, and renderer fallbacks so existing history is corrected without migration.

Add regressions for full cache hits, cache writes, mixed Runtime aggregation, and persisted conversation/system usage. Focused validation passed 41 tests; repository-wide checks were blocked by concurrent work-mode changes.

Release note: 修复 OpenCode 缓存命中率偏高或完全命中时显示为空的问题，已有用量记录在重新查询时按完整输入量计算。

src/main/assistant/assistant-database.ts

@@ -5918,6 +5918,13 @@ export class AssistantDatabase {
   }
 
   getTokenUsageSummary(): TokenUsageSummary {
+    // OpenCode reports uncached input for every provider, including OpenAI.
+    const cacheInputSql = `usage.input_tokens + CASE
+      WHEN usage.runtime = 'opencode'
+        OR LOWER(usage.provider) LIKE '%anthropic%'
+      THEN usage.cache_read_tokens + usage.cache_write_tokens
+      ELSE 0
+    END`
     const systemSourceSql = `CASE
              WHEN tasks.conversation_id LIKE 'heartbeat:%' THEN 'heartbeat'
              WHEN tasks.conversation_id LIKE 'supervision:%' THEN 'supervision'
@@ -5947,14 +5954,7 @@ export class AssistantDatabase {
              SUM(usage.output_tokens) AS output_tokens,
              SUM(usage.cache_read_tokens) AS cache_read_tokens,
              SUM(usage.cache_write_tokens) AS cache_write_tokens,
-             SUM(
-               usage.input_tokens +
-               CASE
-                 WHEN LOWER(usage.provider) LIKE '%anthropic%'
-                 THEN usage.cache_read_tokens + usage.cache_write_tokens
-                 ELSE 0
-               END
-             ) AS cache_input_tokens
+             SUM(${cacheInputSql}) AS cache_input_tokens
            FROM model_usage_calls usage
            JOIN tasks ON tasks.id = usage.request_id
            LEFT JOIN projects ON projects.id = tasks.project_id
@@ -6017,17 +6017,7 @@ export class AssistantDatabase {
            COALESCE(SUM(usage.output_tokens), 0) AS output_tokens,
            COALESCE(SUM(usage.cache_read_tokens), 0) AS cache_read_tokens,
            COALESCE(SUM(usage.cache_write_tokens), 0) AS cache_write_tokens,
-           COALESCE(
-             SUM(
-               usage.input_tokens +
-               CASE
-                 WHEN LOWER(usage.provider) LIKE '%anthropic%'
-                 THEN usage.cache_read_tokens + usage.cache_write_tokens
-                 ELSE 0
-               END
-             ),
-             0
-           ) AS cache_input_tokens
+           COALESCE(SUM(${cacheInputSql}), 0) AS cache_input_tokens
          FROM model_usage_calls usage
          LEFT JOIN tasks ON tasks.id = usage.request_id
          GROUP BY is_system`