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