diff --git a/src/lib/calibration/__tests__/validation.test.ts b/src/lib/calibration/__tests__/validation.test.ts
new file mode 100644
index 0000000..c348905
--- /dev/null
+++ b/src/lib/calibration/__tests__/validation.test.ts
@@ -0,0 +1,53 @@
+import { describe, expect, it } from "vitest";
+
+import {
+  manualPerformanceInputSchema,
+  performanceSnapshotSchema,
+  publicationInputSchema,
+} from "../validation";
+
+describe("calibration validation", () => {
+  it("accepts a publication URL and normalizes optional notes", () => {
+    const parsed = publicationInputSchema.parse({
+      platform: "official_site",
+      url: "https://example.com/articles/geo",
+      published_at: "2026-06-24T12:00:00.000Z",
+      notes: " 官网首发 ",
+    });
+
+    expect(parsed.platform).toBe("official_site");
+    expect(parsed.notes).toBe("官网首发");
+  });
+
+  it("keeps sparse manual metrics absent instead of turning them into zeroes", () => {
+    const parsed = manualPerformanceInputSchema.parse({
+      window_label: "T+7d",
+      views: "1200",
+      clicks: "",
+      inquiries: undefined,
+      comments: "3",
+      feedback_summary: "用户追问案例依据",
+    });
+
+    expect(parsed.metrics).toEqual({
+      views: 1200,
+      comments: 3,
+    });
+    expect(parsed.feedback_summary).toBe("用户追问案例依据");
+  });
+
+  it("rejects unsafe raw adapter credentials in snapshots", () => {
+    expect(() =>
+      performanceSnapshotSchema.parse({
+        id: "perf_test",
+        publication_id: "pub_test",
+        source: "manual",
+        window_label: "T+3d",
+        metrics: { views: 10 },
+        feedback_summary: "",
+        raw_reference: "cookie=sessionid=secret",
+        snapshot_at: "2026-06-24T12:00:00.000Z",
+      }),
+    ).toThrow(/raw_reference/);
+  });
+});
diff --git a/src/lib/calibration/types.ts b/src/lib/calibration/types.ts
new file mode 100644
index 0000000..62db10f
--- /dev/null
+++ b/src/lib/calibration/types.ts
@@ -0,0 +1,100 @@
+import type { PublishPlatform, QaReport } from "../domain/types";
+
+export type CalibrationDirection =
+  | "better_than_expected"
+  | "as_expected"
+  | "worse_than_expected"
+  | "needs_more_data";
+
+export type PerformanceSource = "manual" | `adapter:${string}`;
+
+export interface RubricDimension {
+  id: string;
+  label: string;
+  weight: number;
+  description: string;
+}
+
+export interface RubricVersion {
+  id: string;
+  version: string;
+  name: string;
+  dimensions: RubricDimension[];
+  formula: "weighted_average_0_to_10";
+  is_active: boolean;
+  created_at: string;
+}
+
+export interface ScoringRun {
+  id: string;
+  job_id: string;
+  revision: number;
+  rubric_version_id: string;
+  dimension_scores: Record<string, number>;
+  composite_score: number;
+  rationale: string;
+  created_at: string;
+}
+
+export interface PublicationRecord {
+  id: string;
+  job_id: string;
+  revision: number;
+  platform: PublishPlatform;
+  url: string;
+  published_at: string;
+  status: "draft" | "published" | "archived";
+  notes: string;
+  created_at: string;
+  updated_at: string;
+}
+
+export interface PerformanceMetrics {
+  views?: number;
+  impressions?: number;
+  clicks?: number;
+  inquiries?: number;
+  likes?: number;
+  comments?: number;
+  shares?: number;
+  saves?: number;
+  average_position?: number;
+}
+
+export interface PerformanceSnapshot {
+  id: string;
+  publication_id: string;
+  source: PerformanceSource;
+  window_label: string;
+  metrics: PerformanceMetrics;
+  feedback_summary: string;
+  raw_reference?: string;
+  snapshot_at: string;
+}
+
+export interface CalibrationEvent {
+  id: string;
+  publication_id: string;
+  scoring_run_id: string;
+  performance_snapshot_id: string;
+  direction: CalibrationDirection;
+  observations: string[];
+  recommended_action: string;
+  created_at: string;
+}
+
+export interface AdapterFetchInput {
+  publication: PublicationRecord;
+  window_label: string;
+}
+
+export interface PerformanceAdapter {
+  source: PerformanceSource;
+  fetch(input: AdapterFetchInput): Promise<PerformanceSnapshot>;
+}
+
+export interface CalibrationContext {
+  scoringRun: ScoringRun;
+  qaReport: QaReport;
+  snapshot: PerformanceSnapshot;
+}
diff --git a/src/lib/calibration/validation.ts b/src/lib/calibration/validation.ts
new file mode 100644
index 0000000..c948def
--- /dev/null
+++ b/src/lib/calibration/validation.ts
@@ -0,0 +1,157 @@
+import { z } from "zod";
+
+import { publishPlatformSchema } from "../domain/validation";
+import type {
+  CalibrationDirection,
+  CalibrationEvent,
+  PerformanceMetrics,
+  PerformanceSnapshot,
+  PerformanceSource,
+  PublicationRecord,
+  RubricVersion,
+  ScoringRun,
+} from "./types";
+
+const optionalTextSchema = z
+  .preprocess((value) => (value == null ? "" : value), z.string())
+  .transform((value) => value.trim());
+
+function optionalMetric(value: unknown) {
+  if (value == null || value === "") return undefined;
+  const numberValue = typeof value === "number" ? value : Number(value);
+  return Number.isFinite(numberValue) && numberValue >= 0 ? numberValue : value;
+}
+
+const metricsShape = {
+  views: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  impressions: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  clicks: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  inquiries: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  likes: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  comments: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  shares: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  saves: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+  average_position: z.preprocess(optionalMetric, z.number().nonnegative().optional()),
+};
+
+export const performanceMetricsSchema = z
+  .object(metricsShape)
+  .transform(
+    (metrics) =>
+      Object.fromEntries(
+        Object.entries(metrics).filter(([, value]) => value !== undefined),
+      ) as PerformanceMetrics,
+  );
+
+export const publicationInputSchema = z.object({
+  platform: publishPlatformSchema,
+  url: z.string().trim().url(),
+  published_at: z.string().datetime(),
+  notes: optionalTextSchema.default(""),
+});
+
+export const manualPerformanceInputSchema = z
+  .object({
+    window_label: z.string().trim().min(1),
+    feedback_summary: optionalTextSchema.default(""),
+    raw_reference: optionalTextSchema.optional(),
+    ...metricsShape,
+  })
+  .transform(({ window_label, feedback_summary, raw_reference, ...metrics }) => ({
+    window_label,
+    feedback_summary,
+    raw_reference: raw_reference || undefined,
+    metrics: performanceMetricsSchema.parse(metrics),
+  }));
+
+function isPerformanceSource(value: unknown): value is PerformanceSource {
+  return (
+    value === "manual" ||
+    (typeof value === "string" &&
+      value.startsWith("adapter:") &&
+      value.length > "adapter:".length)
+  );
+}
+
+function rejectUnsafeRawReference(value: string | undefined) {
+  if (!value) return value;
+  if (/cookie|sessionid|token|secret|api[_-]?key|authorization/i.test(value)) {
+    throw new Error("raw_reference must not contain credentials");
+  }
+  return value;
+}
+
+export const rubricVersionSchema = z.object({
+  id: z.string().trim().min(1),
+  version: z.string().trim().min(1),
+  name: z.string().trim().min(1),
+  dimensions: z.array(
+    z.object({
+      id: z.string().trim().min(1),
+      label: z.string().trim().min(1),
+      weight: z.number().positive(),
+      description: z.string().trim().min(1),
+    }),
+  ),
+  formula: z.literal("weighted_average_0_to_10"),
+  is_active: z.boolean(),
+  created_at: z.string().datetime(),
+}) satisfies z.ZodType<RubricVersion>;
+
+export const scoringRunSchema = z.object({
+  id: z.string().trim().min(1),
+  job_id: z.string().trim().min(1),
+  revision: z.number().int().positive(),
+  rubric_version_id: z.string().trim().min(1),
+  dimension_scores: z.record(z.string(), z.number().min(0).max(5)),
+  composite_score: z.number().min(0).max(10),
+  rationale: z.string().trim(),
+  created_at: z.string().datetime(),
+}) satisfies z.ZodType<ScoringRun>;
+
+export const publicationRecordSchema = z.object({
+  id: z.string().trim().min(1),
+  job_id: z.string().trim().min(1),
+  revision: z.number().int().positive(),
+  platform: publishPlatformSchema,
+  url: z.string().trim().url(),
+  published_at: z.string().datetime(),
+  status: z.enum(["draft", "published", "archived"]),
+  notes: z.string().trim(),
+  created_at: z.string().datetime(),
+  updated_at: z.string().datetime(),
+}) satisfies z.ZodType<PublicationRecord>;
+
+export const performanceSnapshotSchema = z
+  .object({
+    id: z.string().trim().min(1),
+    publication_id: z.string().trim().min(1),
+    source: z.custom<PerformanceSource>(isPerformanceSource),
+    window_label: z.string().trim().min(1),
+    metrics: performanceMetricsSchema,
+    feedback_summary: z.string().trim(),
+    raw_reference: z.string().trim().optional(),
+    snapshot_at: z.string().datetime(),
+  })
+  .transform((snapshot) => ({
+    ...snapshot,
+    raw_reference: rejectUnsafeRawReference(snapshot.raw_reference),
+  })) satisfies z.ZodType<PerformanceSnapshot>;
+
+export const calibrationDirectionSchema = z.enum([
+  "better_than_expected",
+  "as_expected",
+  "worse_than_expected",
+  "needs_more_data",
+]) satisfies z.ZodType<CalibrationDirection>;
+
+export const calibrationEventSchema = z.object({
+  id: z.string().trim().min(1),
+  publication_id: z.string().trim().min(1),
+  scoring_run_id: z.string().trim().min(1),
+  performance_snapshot_id: z.string().trim().min(1),
+  direction: calibrationDirectionSchema,
+  observations: z.array(z.string().trim().min(1)),
+  recommended_action: z.string().trim().min(1),
+  created_at: z.string().datetime(),
+}) satisfies z.ZodType<CalibrationEvent>;