refactor: remove as= override and render data-spark at runtime

- Drop resolveBlockAs and the as= attribute; scanDoc now switches
  directly on role and warns on unknown roles instead of silently
  stripping
- md-table derives data-spark from its loaded CSV via
  parseSparkTableCsv; delete injectSparkDirectives and the second
  registry pass so pathIndex is exactly scanDoc output
- Align spark-table dice header regex with isSparkTableHeader

src/components/md-table.tsx

@@ -10,10 +10,11 @@ import {
 import { parseMarkdown } from "../markdown";
 import { parseCSVString, CSV, processVariables } from "./utils/csv-loader";
 import { resolveContentRef } from "./utils/resolve-content";
+import { parseSparkTableCsv } from "./utils/spark-table";
 import {
   areAllLabelsNumeric,
   weightedRandomIndex,
-} from "./utils/weighted-random";
+} from "./utils/weighted-random";;
 
 export interface TableProps {
   roll?: boolean;
@@ -59,16 +60,23 @@ customElement(
         if (content === null) {
           throw new Error(`Failed to resolve table content: "${ref}"`);
         }
-        return parseCSVString(content);
+        return content;
       },
     );
 
-    // 当数据加载完成后更新 rows
+    // 当数据加载完成后更新 rows，并为火花表设置 data-spark（供 RevealManager
+    // 悬停触发 /roll）。data-spark 在渲染时派生，不在扫描时注入。
     createEffect(() => {
-      const data = csvData();
-      if (data) {
-        // 将加载的数据赋值给 rows，CSV 类型已经包含 sourcePath 等属性
-        setRows(data as unknown as CSV<TableRow>);
+      const content = csvData();
+      if (!content) return;
+      setRows(parseCSVString(content) as unknown as CSV<TableRow>);
+      if (element) {
+        const meta = parseSparkTableCsv(content);
+        if (meta) {
+          element.setAttribute("data-spark", meta.slug);
+        } else {
+          element.removeAttribute("data-spark");
+        }
       }
     });