diff --git a/src/lib/domain/__tests__/validation.test.ts b/src/lib/domain/__tests__/validation.test.ts
index 93fa23e..910a36b 100644
--- a/src/lib/domain/__tests__/validation.test.ts
+++ b/src/lib/domain/__tests__/validation.test.ts
@@ -77,6 +77,42 @@ describe("domain validation", () => {
     expect(numericExperience.experience_years).toBe(8);
   });
 
+  it("normalizes object-shaped and single-string LLM fact card fields", () => {
+    const parsed = candidateFactCardSchema.parse({
+      company_full_name: { name: "示例科技有限公司" },
+      company_short_names: "示例科技",
+      brand_names: [{ name: "示例品牌" }],
+      product_names: [{ product: "GEO内容优化平台" }],
+      target_industry: { industry: "GEO内容优化" },
+      target_audience: { audience: "市场团队" },
+      experience_years: { years: "8年" },
+      core_claims: [
+        { claim: "提供GEO内容优化服务", source: "原文明确出现" },
+      ],
+      forbidden_claims: [
+        { claim: "行业第一", reason: "缺少第三方依据" },
+      ],
+      image_topics: [{ topic: "产品后台截图" }],
+      uncertain_items: [
+        { item: "客户案例", reason: "原文没有给出客户名称" },
+        { claim: "出海能力", evidence: "只出现营销表述" },
+      ],
+    });
+
+    expect(parsed.company_full_name).toBe("示例科技有限公司");
+    expect(parsed.company_short_names).toEqual(["示例科技"]);
+    expect(parsed.brand_names).toEqual(["示例品牌"]);
+    expect(parsed.product_names).toEqual(["GEO内容优化平台"]);
+    expect(parsed.target_industry).toBe("GEO内容优化");
+    expect(parsed.target_audience).toBe("市场团队");
+    expect(parsed.experience_years).toBe(8);
+    expect(parsed.core_claims).toEqual(["提供GEO内容优化服务"]);
+    expect(parsed.forbidden_claims).toEqual(["行业第一"]);
+    expect(parsed.image_topics).toEqual(["产品后台截图"]);
+    expect(parsed.uncertain_items).toEqual(["客户案例", "出海能力"]);
+    expect(parsed.is_ready_for_optimization).toBe(false);
+  });
+
   it("keeps incomplete candidate fact cards editable and ready", () => {
     const parsed = candidateFactCardSchema.parse({
       company_full_name: "",
diff --git a/src/lib/domain/validation.ts b/src/lib/domain/validation.ts
index 64cd6a6..c57927e 100644
--- a/src/lib/domain/validation.ts
+++ b/src/lib/domain/validation.ts
@@ -52,19 +52,129 @@ export const articleInputSchema = z.object({
   user_instructions: z.string().trim().default(""),
 }) satisfies z.ZodType<ArticleInput>;
 
-const stringOrStringArraySchema = z.preprocess((value) => {
+function isPlainRecord(value: unknown): value is Record<string, unknown> {
+  return Boolean(value) && typeof value === "object" && !Array.isArray(value);
+}
+
+function firstStringField(record: Record<string, unknown>, keys: string[]) {
+  for (const key of keys) {
+    const value = record[key];
+    if (typeof value === "string" && value.trim().length > 0) {
+      return value.trim();
+    }
+    if (typeof value === "number" && Number.isFinite(value)) {
+      return String(value);
+    }
+  }
+  return null;
+}
+
+const llmStringKeys = [
+  "value",
+  "text",
+  "name",
+  "title",
+  "summary",
+  "claim",
+  "item",
+  "topic",
+  "audience",
+  "industry",
+  "company",
+  "company_name",
+  "brand",
+  "product",
+  "product_name",
+  "content",
+  "body",
+  "markdown",
+  "body_markdown",
+  "reason",
+  "description",
+  "evidence",
+  "source",
+  "suggestion",
+  "fix",
+  "change",
+  "changed",
+  "after",
+];
+
+function normalizedStringOrNull(value: unknown) {
+  const normalized = normalizeStringValue(value);
+  return typeof normalized === "string" && normalized.trim().length > 0
+    ? normalized.trim()
+    : null;
+}
+
+function normalizeStringValue(value: unknown): unknown {
+  if (typeof value === "string") return value.trim();
+  if (typeof value === "number" && Number.isFinite(value)) return String(value);
   if (Array.isArray(value)) {
     return value
-      .map((item) => (typeof item === "string" ? item.trim() : ""))
-      .filter(Boolean)
+      .map(normalizedStringOrNull)
+      .filter((item): item is string => Boolean(item))
       .join("、");
   }
-  return value;
-}, z.string().trim());
+  if (!isPlainRecord(value)) return value;
 
-const experienceYearsSchema = z.preprocess((value) => {
-  if (typeof value !== "string") return value;
-  const trimmed = value.trim();
+  const direct = firstStringField(value, llmStringKeys);
+  if (direct) return direct;
+
+  const stringValues = Object.values(value)
+    .map(normalizedStringOrNull)
+    .filter((item): item is string => Boolean(item));
+  return stringValues.join("；");
+}
+
+function normalizeStringList(value: unknown): unknown {
+  if (value == null) return [];
+  const items = Array.isArray(value) ? value : [value];
+  return items
+    .map(normalizedStringOrNull)
+    .filter((item): item is string => Boolean(item));
+}
+
+const llmStringSchema = z.preprocess(normalizeStringValue, z.string().trim());
+
+const requiredLlmStringSchema = z.preprocess(
+  normalizeStringValue,
+  z.string().trim().min(1),
+);
+
+const optionalLlmStringSchema = z.preprocess((value) => {
+  if (value == null) return "";
+  return normalizeStringValue(value);
+}, z.string().trim().default(""));
+
+const stringListSchema = z.preprocess(
+  normalizeStringList,
+  z.array(z.string().trim().min(1)).default([]),
+);
+
+function normalizeExperienceYears(value: unknown): unknown {
+  let candidate = value;
+  if (Array.isArray(candidate)) {
+    candidate = candidate[0] ?? null;
+  }
+  if (isPlainRecord(candidate)) {
+    for (const key of ["years", "year", "experience_years", "value"]) {
+      const entry = candidate[key];
+      if (typeof entry === "number" && Number.isFinite(entry)) return entry;
+    }
+    candidate =
+      firstStringField(candidate, [
+        "years",
+        "year",
+        "experience_years",
+        "value",
+        "text",
+        "description",
+      ]) ?? candidate;
+  }
+  if (typeof candidate !== "string") return candidate;
+
+  const trimmed = candidate.trim();
   if (
     trimmed === "" ||
     /^(?:unknown|none|null|n\/a|not\s+specified|不详|不明确|未知|无)$/i.test(
@@ -74,21 +184,26 @@ const experienceYearsSchema = z.preprocess((value) => {
     return null;
   }
   const yearMatch = trimmed.match(/\d{1,3}/);
-  return yearMatch ? Number(yearMatch[0]) : value;
-}, z.number().int().nonnegative().nullable().default(null));
+  return yearMatch ? Number(yearMatch[0]) : candidate;
+}
+
+const experienceYearsSchema = z.preprocess(
+  normalizeExperienceYears,
+  z.number().int().nonnegative().nullable().default(null),
+);
 
 const factCardBaseSchema = z.object({
-  company_full_name: z.string().trim(),
-  company_short_names: z.array(z.string().trim().min(1)).default([]),
-  brand_names: z.array(z.string().trim().min(1)).default([]),
-  product_names: z.array(z.string().trim().min(1)).default([]),
-  target_industry: z.string().trim(),
-  target_audience: stringOrStringArraySchema,
+  company_full_name: llmStringSchema,
+  company_short_names: stringListSchema,
+  brand_names: stringListSchema,
+  product_names: stringListSchema,
+  target_industry: llmStringSchema,
+  target_audience: llmStringSchema,
   experience_years: experienceYearsSchema,
-  core_claims: z.array(z.string().trim().min(1)).default([]),
-  forbidden_claims: z.array(z.string().trim().min(1)).default([]),
-  image_topics: z.array(z.string().trim().min(1)).default([]),
-  uncertain_items: z.array(z.string().trim().min(1)).default([]),
+  core_claims: stringListSchema,
+  forbidden_claims: stringListSchema,
+  image_topics: stringListSchema,
+  uncertain_items: stringListSchema,
 });
 
 export const candidateFactCardSchema = factCardBaseSchema
@@ -117,16 +232,6 @@ export const imageSuggestionSchema = z.object({
   suggestion: z.string().trim().min(1),
 });
 
-function firstStringField(record: Record<string, unknown>, keys: string[]) {
-  for (const key of keys) {
-    const value = record[key];
-    if (typeof value === "string" && value.trim().length > 0) {
-      return value.trim();
-    }
-  }
-  return null;
-}
-
 function normalizeChangedSection(value: unknown) {
   if (!value || typeof value !== "object" || Array.isArray(value)) {
     return value;