/** * SB-S3c — the cross-silo assembler (the payoff). * * Answers the arc's north-star query (`architecture.md:17`): *which raw material * actually performs?* — `specific → post → measured analytics`. The post record * (`ingest/published/.md`) already carries the `specifics`/`trends` ids * it was built from (SB-S3c hub-side threading); this module joins each post to * its measured analytics row and surfaces the whole graph. * * PURE core: `assemblePostGraph({records, analytics})` takes already-loaded inputs * and returns the graph — no FS/clock/network. The analytics↔post join is an honest * HEURISTIC, never a guaranteed key: analytics carries no body and no URN (only a * title-prefix + date), so `matchRow` joins by normalized title-prefix + date with * explicit confidence tiers (`high`/`low`/`none`) — a real-CSV `none` is a * normalization-tightening signal, not a proof of no match. * * DECOUPLED: this module treats tributary ids as opaque 12-hex strings and takes a * minimal `AnalyticsRowInput` shape — it never imports the analytics/trends/ * specifics packages. The thin read-only `loadAnalyticsRows` IO inlines a raw-JSON * read of the shared data-root (NOT the analytics package's `loadAllPosts`). */ import { existsSync, readFileSync, readdirSync } from "node:fs"; import { join } from "node:path"; import { dataRoot } from "./dataRoot.js"; import type { PublishedRecord } from "./ingest.js"; /** * The minimal analytics-row shape the resolver needs, extracted from the raw * `AnalyticsBatch.posts[]` JSON (`analytics/src/models/types.ts`). Note the field * is `publishedDate` (analytics) vs `published_date` (the brain record). */ export interface AnalyticsRowInput { title: string; publishedDate: string; // YYYY-MM-DD metrics?: { engagementRate?: number } & Record; } export type MatchConfidence = "high" | "low" | "none"; /** A post's matched analytics: the WHOLE row reference (FIX 4), or none. */ export interface PostMatch { confidence: MatchConfidence; row?: AnalyticsRowInput; } export interface PostGraphNode { contentId: string; published_date: string; specifics: string[]; trends: string[]; match: PostMatch; } /** * Minimum normalized-title length to attempt a prefix match. The hook quality-rule * floor is 110 chars; 24 normalized chars (~3–5 words) is the shortest opener * specific enough that a prefix-match is not coincidental, while staying well under * any real hook. Below floor → `none` (an operator can still eyeball). */ const PREFIX_FLOOR = 24; /** Brain-local copy of the specifics-bank `normalizeContent` idiom (NOT imported). */ export function normalize(s: string): string { return s.trim().toLowerCase().replace(/\s+/g, " "); } /** Strip a trailing LinkedIn truncation marker (`…`/`...`) so a `…`-suffixed export title still prefix-matches. */ function stripTrailingEllipsis(s: string): string { return s.replace(/(?:…|\.{3})\s*$/, "").trimEnd(); } /** * Match one analytics row to one published record. Returns the tiered match, or * `null` when the row does not qualify (no prefix / below floor) — STUB until S3c * Step 3. */ export function matchRow(record: PublishedRecord, row: AnalyticsRowInput): PostMatch | null { const nt = stripTrailingEllipsis(normalize(row.title)); if (nt.length < PREFIX_FLOOR) return null; // too short to discriminate → none if (!normalize(record.body).startsWith(nt)) return null; // no prefix → none const confidence: MatchConfidence = record.published_date === row.publishedDate ? "high" : "low"; return { confidence, row }; } /** * Assemble the post → raw-material → performance graph. Pure (no FS/clock/network). * For each record, the BEST qualifying analytics row: `high` (same date) beats `low` * (different date); within a tier, the longest matched title wins. The analytics rows * are sorted once (publishedDate desc, title asc) so an exact-length tie is stable — * never `readdirSync`-order-dependent. */ export function assemblePostGraph(args: { records: PublishedRecord[]; analytics: AnalyticsRowInput[]; }): PostGraphNode[] { const analytics = [...args.analytics].sort( (a, b) => b.publishedDate.localeCompare(a.publishedDate) || a.title.localeCompare(b.title), ); return args.records.map((record) => { let best: PostMatch | null = null; let bestLen = -1; for (const row of analytics) { const m = matchRow(record, row); if (!m) continue; const len = stripTrailingEllipsis(normalize(row.title)).length; const better = best === null || (m.confidence === "high" && best.confidence === "low") || (m.confidence === best.confidence && len > bestLen); if (better) { best = m; bestLen = len; } } return { contentId: record.id, published_date: record.published_date, specifics: record.specifics, trends: record.trends, match: best ?? { confidence: "none" }, }; }); } /** * Read-only loader: inline a raw-JSON read of the analytics batches under the shared * data-root and extract the minimal row shape. STUB until S3c Step 3. * * NOTE (root-skew caveat): resolves via the brain `dataRoot` (`${LINKEDIN_STUDIO_DATA}/ * analytics/posts`); the analytics package additionally honours the deprecated * `ANALYTICS_ROOT` override, which this path does NOT — if set to a non-default * path, the join degrades to every-post-`none` (accepted cost of the no-import * decoupling; the M0 default leaves `ANALYTICS_ROOT` unset). */ export function loadAnalyticsRows(): AnalyticsRowInput[] { const dir = dataRoot(join("analytics", "posts")); if (!existsSync(dir)) return []; // fresh-clone / no imports yet → no rows const rows: AnalyticsRowInput[] = []; for (const name of readdirSync(dir)) { if (!name.endsWith(".json") || name.startsWith(".")) continue; try { const batch = JSON.parse(readFileSync(join(dir, name), "utf8")) as { posts?: unknown[] }; for (const p of batch?.posts ?? []) { const row = p as Partial; if (typeof row?.title === "string" && typeof row?.publishedDate === "string") { rows.push({ title: row.title, publishedDate: row.publishedDate, metrics: row.metrics }); } } } catch { // skip a malformed/unreadable batch file — never crash (mirrors listPublished) } } return rows; }