/**
 * item-intel-service — deterministic, description-fuzzy intel for any
 * quote_item or order_item. Powers the ⓘ popover (Option A — replaces
 * the older `ItemHistoryPopover` content).
 *
 * ## What it answers for one item
 *
 *   - "Do we have it in stock?"           → stock_list (fuzzy stock_items)
 *   - "Did we buy it before, and from whom?" → supplier_history
 *                                             (last order per unique
 *                                              supplier, via
 *                                              stock_purchase_items ↔
 *                                              stock_purchases)
 *   - "Is it on our price list?"          → price_list (fuzzy price_list,
 *                                            ranked by overlapScore on
 *                                            the denormalised search_text)
 *   - "Have we quoted it before?"         → recent_quote (fuzzy quote_items)
 *   - "Have we ordered it before?"        → recent_order (fuzzy order_items)
 *
 * ## Matching strategy (description-fuzzy, no SKU gate)
 *
 * New items don't have a SKU. The previous SKU-first services
 * (`getItemHistory`, `populateQuoteItemInsights`) returned empty for
 * every section whenever no SKU match could be recovered via the
 * description-fuzzy SKU recovery. This service runs the description
 * fuzzy match against each section's collection directly, so brand
 * new items with only a free-text description still get intel.
 *
 * The candidate pull for stock_items, quote_items, and order_items
 * uses PB's `~` operator with an OR of the top informative tokens.
 * In-app Jaccard + overlapScore then rank the candidates. Price list
 * uses the same OR but on a multi-column candidate filter
 * (description + search_text + sku + sku_normalised) since its
 * `search_text` field is the denormalised token soup the Catalogue
 * tab already relies on.
 *
 * ## Per-section limits (the popover must stay scannable)
 *
 *   stock_list       → 3 rows
 *   supplier_history → one row per unique supplier (latest purchase)
 *   price_list       → 5 rows
 *   recent_quote     → 2 rows
 *   recent_order     → 2 rows
 *
 * Empty sections are `[]`, never padded.
 *
 * ## Stock display vs purchase-cap decoupling
 *
 * Stock list displays the top 3 by fuzzy score. But the supplier
 * dedup needs purchase history from ALL stock_items that fuzzy-match
 * (not just the top 3), otherwise legitimate suppliers we bought
 * from get hidden behind a low stock score. The SPI walk uses a
 * wider cap (10) and runs in parallel.
 *
 * ## Auth + writes
 *
 * Uses admin PB client. Writes `quote_items.ai_item_insights` or
 * `order_items.ai_item_insights` directly. Idempotent — safe to
 * re-run. The MCP `populate_insights` tool delegates here.
 */

import { getAdminPocketBase } from "@/lib/server/pocketbase-admin";
import { jaccard } from "@/lib/server/order-quote-match";
import type {
  ItemIntel,
  ItemIntelPriceListRow,
  ItemIntelQuoteRow,
  ItemIntelOrderRow,
  ItemIntelStockRow,
  ItemIntelSupplierRow,
  ItemIntelTarget,
} from "@/lib/types";
import { ITEM_INTEL_LIMITS } from "@/lib/types";

// ─── Pure scoring helpers ────────────────────────────────────────────

/** Tokenizer tuned for item-intel fuzzy matching.
 *
 *  Differs from `order-quote-match.tokenize` in three ways that
 *  matter for catalogue fuzziness:
 *
 *    1. Keeps short numeric tokens ("50", "20L", "M20") — these
 *       carry product identity (sizes, capacities, model numbers).
 *       Dropping them made every SAE oil tie at overlap=1.0 and
 *       ruined price_list matching against the AFRIQ SKUs.
 *    2. Smaller stopword set — only tokens that are pure noise
 *       across every catalogue. No "mm" / "qty" filter because
 *       "qty" doesn't appear in our descriptions and "mm" only
 *       does so meaningfully (e.g. "M6 X 30MM" — keep it).
 *    3. Allows single-character numeric tokens ("L", "5") so
 *       compound unit strings like "20LT" or "5L" tokenise as
 *       one unit token (the regex matches the whole run, not
 *       per-character).
 */
const INTEL_STOPWORDS = new Set([
  "the", "and", "with", "for", "of", "to", "a", "an", "in", "on", "at",
  "by", "from", "as", "is", "or", "x",
]);
function tokenizeIntel(s: string): Set<string> {
  const out = new Set<string>();
  if (!s) return out;
  for (const tok of String(s).toLowerCase().match(/[a-z0-9]+/g) || []) {
    if (INTEL_STOPWORDS.has(tok)) continue;
    out.add(tok);
  }
  return out;
}

/** Overlap coefficient: |A ∩ B| / min(|A|, |B|).
 *  Better than Jaccard for "short query against a rich candidate" —
 *  doesn't penalise extra tokens on the candidate side. Used for
 *  ranking against the price_list `search_text` blob. */
function overlapScore(a: Set<string>, b: Set<string>): number {
  if (a.size === 0 || b.size === 0) return 0;
  let inter = 0;
  for (const t of a) if (b.has(t)) inter++;
  return inter / Math.min(a.size, b.size);
}

/** Days between `iso` and `now`. Negative clamped to 0. */
function daysAgo(iso: string | null | undefined): number {
  if (!iso) return 0;
  const t = new Date(iso).getTime();
  if (Number.isNaN(t)) return 0;
  const diffMs = Date.now() - t;
  return diffMs <= 0 ? 0 : Math.floor(diffMs / 86_400_000);
}

/** Drop stopwords + short tokens. */
const INFORMATIVE_MIN_LEN = 3;

/** Pick the top N tokens by length desc (most distinctive first). */
function informativeTokens(s: string, max = 4): string[] {
  const toks = tokenizeIntel(s || "");
  return [...toks]
    .filter((t) => !INTEL_STOPWORDS.has(t) && t.length >= INFORMATIVE_MIN_LEN)
    .sort((a, b) => b.length - a.length)
    .slice(0, max);
}

/** PocketBase `~` is case-insensitive substring match. OR'ing the top
 *  informative tokens keeps the candidate set broad while letting
 *  the in-app Jaccard/overlap rank with precision. */
function buildPbContainsOR(field: string, targetDesc: string, maxTokens = 4): string {
  const toks = informativeTokens(targetDesc, maxTokens);
  if (toks.length === 0) return "";
  return toks.map((t) => `${field} ~ "${t}"`).join(" || ");
}

/** Combined Jaccard + overlap score, capped at 1. */
function combinedScore(a: Set<string>, b: Set<string>): number {
  return Math.max(jaccard(a, b), overlapScore(a, b));
}

// ─── PB I/O helpers ───────────────────────────────────────────────────

type PbListResult<T> = { items: T[]; totalItems?: number };

async function safeGetList<T>(
  pb: ReturnType<typeof Object> extends never ? never : Awaited<ReturnType<typeof getAdminPocketBase>>,
  collection: string,
  opts: { max?: number; filter?: string; sort?: string; fields?: string; expand?: string },
  fallback: PbListResult<T> = { items: [] },
): Promise<PbListResult<T>> {
  try {
    return (await pb.collection(collection).getList(1, opts.max ?? 300, opts)) as PbListResult<T>;
  } catch (err) {
    const status = (err as { status?: number })?.status;
    if (status === 400 || status === 404) {
      console.warn(`[item-intel] ${collection} returned ${status} — degrading`);
      return fallback;
    }
    throw err;
  }
}

async function loadSuppliersById(pb: Awaited<ReturnType<typeof getAdminPocketBase>>): Promise<Map<string, string>> {
  try {
    const rows = await pb
      .collection("suppliers")
      .getFullList<{ id: string; suppliername: string }>({ fields: "id,suppliername", batch: 500 });
    return new Map(rows.map((s) => [s.id, s.suppliername]));
  } catch {
    return new Map();
  }
}

// ─── The 5 sections ──────────────────────────────────────────────────

async function buildStock(
  pb: Awaited<ReturnType<typeof getAdminPocketBase>>,
  target: { id: string; description: string },
  supplierNameById: Map<string, string>,
): Promise<{ matches: ItemIntelStockRow[]; purchaseHistory: Array<{
  stock_item_id: string;
  stock_item_sku: string;
  stock_item_name: string;
  supplier_id: string;
  supplier_name: string;
  cost_price: number;
  quantity: number;
  purchased_at: string;
  days_ago: number;
  purchase_number: string;
}> }> {
  const filter = buildPbContainsOR("description", target.description);
  if (!filter) return { matches: [], purchaseHistory: [] };

  const candRows = await safeGetList<{
    id: string; sku: string; name: string; description: string;
    cost_price: number; selling_price: number; current_qty: number;
    min_qty: number | null; supplier: string;
  }>(pb, "stock_items", {
    filter,
    fields: "id,sku,name,description,cost_price,selling_price,current_qty,min_qty,supplier",
    max: 500,
  });

  const targetTokens = tokenizeIntel(target.description);
  const rankedAll = candRows.items
    .map((si) => ({ si, score: combinedScore(targetTokens, tokenizeIntel(si.description || "")) }))
    .filter((r) => r.score >= 0.2)
    .sort((a, b) => b.score - a.score);

  const forDisplay = rankedAll.slice(0, ITEM_INTEL_LIMITS.stock);
  const forPurchases = rankedAll.slice(0, 10);

  const matches: ItemIntelStockRow[] = forDisplay.map(({ si, score }) => {
    const current_qty = si.current_qty || 0;
    const min_qty = si.min_qty ?? null;
    let status: ItemIntelStockRow["status"] = "out";
    if (current_qty > 0) status = min_qty != null && current_qty <= min_qty ? "low" : "in_stock";
    return {
      stock_item_id: si.id,
      score: +score.toFixed(3),
      name: si.name || "",
      sku: si.sku || "",
      description: si.description || "",
      qty: current_qty,
      min_qty,
      cost_price: si.cost_price || 0,
      selling_price: si.selling_price || 0,
      supplier_id: si.supplier || "",
      supplier_name: supplierNameById.get(si.supplier) || si.supplier || "",
      status,
    };
  });

  const purchaseHistory: Array<{
    stock_item_id: string; stock_item_sku: string; stock_item_name: string;
    supplier_id: string; supplier_name: string;
    cost_price: number; quantity: number; purchased_at: string; days_ago: number;
    purchase_number: string;
  }> = (await Promise.all(
    forPurchases.map(async ({ si }) => {
      try {
        const spiRows = await pb
          .collection("stock_purchase_items")
          .getFullList<{
            id: string; cost_price: number; quantity: number;
            expand?: { purchase?: { id: string; purchase_number: string; supplier: string; created: string } };
          }>({
            filter: `stock_item = "${si.id}"`,
            expand: "purchase",
            fields: "id,cost_price,quantity,expand.purchase.id,expand.purchase.purchase_number,expand.purchase.supplier,expand.purchase.created",
          });
        const out: typeof purchaseHistory = [];
        for (const spi of spiRows) {
          const p = spi.expand?.purchase;
          if (!p) continue;
          out.push({
            stock_item_id: si.id,
            stock_item_sku: si.sku || "",
            stock_item_name: si.name || "",
            supplier_id: p.supplier || "",
            supplier_name: supplierNameById.get(p.supplier) || p.supplier || "",
            cost_price: spi.cost_price || 0,
            quantity: spi.quantity || 0,
            purchased_at: p.created,
            days_ago: daysAgo(p.created),
            purchase_number: p.purchase_number || "",
          });
        }
        return out;
      } catch (err) {
        console.warn(`[item-intel] spi join failed for ${si.id}:`, (err as { status?: number })?.status);
        return [];
      }
    }),
  )).flat();

  purchaseHistory.sort((a, b) => (b.purchased_at || "").localeCompare(a.purchased_at || ""));
  return { matches, purchaseHistory };
}

/** Last order at every unique supplier. Latest purchase wins per
 *  supplier_id; sort by purchased_at desc. The stock_item_* fields
 *  are taken from the most recent purchase row for that supplier —
 *  earlier rows for the same supplier carry older stock_items. */
function buildLastSupplierPrice(purchaseHistory: Array<{
  supplier_id: string; supplier_name: string; cost_price: number;
  purchased_at: string; days_ago: number; purchase_number: string;
  stock_item_id: string; stock_item_sku: string; stock_item_name: string;
}>): ItemIntelSupplierRow[] {
  const bySupplier = new Map<string, {
    supplier_id: string; supplier_name: string; last_cost: number;
    last_bought_at: string; days_ago: number; last_purchase_number: string;
    times_bought: number;
    stock_item_id: string; stock_item_sku: string; stock_item_name: string;
  }>();
  for (const r of purchaseHistory) {
    if (!r.supplier_id) continue;
    const prev = bySupplier.get(r.supplier_id);
    if (!prev) {
      bySupplier.set(r.supplier_id, {
        supplier_id: r.supplier_id,
        supplier_name: r.supplier_name,
        last_cost: r.cost_price,
        last_bought_at: r.purchased_at,
        days_ago: r.days_ago,
        last_purchase_number: r.purchase_number,
        times_bought: 1,
        stock_item_id: r.stock_item_id,
        stock_item_sku: r.stock_item_sku,
        stock_item_name: r.stock_item_name,
      });
    } else {
      prev.times_bought += 1;
      if (new Date(r.purchased_at).getTime() > new Date(prev.last_bought_at).getTime()) {
        prev.last_cost = r.cost_price;
        prev.last_bought_at = r.purchased_at;
        prev.days_ago = r.days_ago;
        prev.last_purchase_number = r.purchase_number;
        prev.stock_item_id = r.stock_item_id;
        prev.stock_item_sku = r.stock_item_sku;
        prev.stock_item_name = r.stock_item_name;
      }
    }
  }
  return [...bySupplier.values()].sort((a, b) =>
    (b.last_bought_at || "").localeCompare(a.last_bought_at || ""),
  );
}

async function buildPriceList(
  pb: Awaited<ReturnType<typeof getAdminPocketBase>>,
  target: { description: string },
): Promise<ItemIntelPriceListRow[]> {
  const toks = informativeTokens(target.description, 4);
  if (toks.length === 0) return [];

  // OR informative tokens across every text column the repo already
  // keeps searchable. `search_text` is the denormalised token soup
  // built by `buildPriceListSearchText` (src/lib/price-list-search.ts)
  // — it's how the Catalogue tab does fuzzy hits and the cheapest
  // way to catch items where the catalogue wording diverges from the
  // operator's wording (e.g. "SAE 50 - 20L" → row "SAE 50 SF/CF4 - 20 LT").
  const cols = ["description", "search_text", "sku", "sku_normalised"];
  const clauses = cols.flatMap((c) => toks.map((t) => `${c} ~ "${t}"`));
  const filter = `(${clauses.join(" || ")})`;

  const candRows = await safeGetList<{
    id: string; sku: string; sku_normalised: string; description: string;
    brand: string; category: string; cost_price: number; selling_price: number;
    supplier: string; source_file: string; updated: string; search_text: string;
  }>(pb, "price_list", {
    filter,
    fields: "id,sku,sku_normalised,description,brand,category,cost_price,selling_price,supplier,source_file,updated,search_text",
    max: 300,
  });

  // Rank with overlapScore against the concatenated text columns —
  // for short queries against a rich denormalised blob, overlap is
  // the right measure (it doesn't penalise extra tokens the way
  // Jaccard does).
  const targetTokens = tokenizeIntel(target.description);
  const ranked: Array<{ row: typeof candRows.items[number]; score: number }> = [];
  for (const r of candRows.items) {
    const haystack = [r.description, r.search_text, r.sku, r.sku_normalised, r.brand, r.category, r.supplier, r.source_file]
      .filter(Boolean).join(" ");
    const score = overlapScore(targetTokens, tokenizeIntel(haystack));
    if (score >= 0.6) ranked.push({ row: r, score });
  }
  ranked.sort((a, b) => b.score - a.score);
  return ranked.slice(0, ITEM_INTEL_LIMITS.priceList).map(({ row: r, score }) => ({
    score: +score.toFixed(3),
    sku: r.sku || "",
    description: r.description || "",
    brand: r.brand || "",
    category: r.category || "",
    cost_price: r.cost_price || 0,
    selling_price: r.selling_price || 0,
    supplier: r.supplier || "",
    source_file: r.source_file || "",
    updated: r.updated,
  }));
}

async function buildQuoteHistory(
  pb: Awaited<ReturnType<typeof getAdminPocketBase>>,
  target: { id: string; description: string },
  supplierNameById: Map<string, string>,
): Promise<ItemIntelQuoteRow[]> {
  const filter = buildPbContainsOR("description", target.description);
  if (!filter) return [];
  const candRows = await safeGetList<{
    id: string; description: string; cost_price: number; selling_price: number;
    quantity: number; created: string; quote: string; supplier: string;
    expand?: {
      quote?: {
        quote_number: string; status: string;
        customer_name?: string; company?: string;
        expand?: { company?: { id: string; company?: string } };
      };
    };
  }>(pb, "quote_items", {
    filter: `id != "${target.id}" && (${filter})`,
    expand: "quote.company",
    fields: "id,description,cost_price,selling_price,quantity,created,quote,supplier,expand.quote.id,expand.quote.quote_number,expand.quote.status,expand.quote.company,expand.quote.expand.company.id,expand.quote.expand.company.company",
    max: 300,
    sort: "-created",
  });
  const targetTokens = tokenizeIntel(target.description);
const ranked = candRows.items
    .map((q) => ({ q, score: combinedScore(targetTokens, tokenizeIntel(q.description || "")) }))
    .filter((r) => r.score >= 0.5)
    .sort((a, b) => b.score - a.score)
    .slice(0, ITEM_INTEL_LIMITS.recentQuote);
  return ranked.map(({ q, score }) => {
    // Resolve the customer/company FKs to human-readable names so the
    // popover doesn't show opaque ids like `vvns7ji6qeao9xk`. Prefer
    // the expanded company name (from the `companies` collection);
    // fall back to the customer name field on the quote, then the raw
    // FK id, then an em-dash.
    const companyName = q.expand?.quote?.expand?.company?.company || "";
    const customerName = q.expand?.quote?.customer_name || "";
    return {
      score: +score.toFixed(3),
      quote_item_id: q.id,
      quote_id: q.quote,
      quote_number: q.expand?.quote?.quote_number || "",
      quote_status: q.expand?.quote?.status || "",
      customer_name: companyName || customerName || q.expand?.quote?.company || "",
      company: companyName || q.expand?.quote?.company || "",
      description: q.description || "",
      cost_price: q.cost_price || 0,
      selling_price: q.selling_price || 0,
      quantity: q.quantity || 0,
      quoted_at: q.created,
      days_ago: daysAgo(q.created),
      supplier_id: q.supplier || "",
      supplier_name: q.supplier
        ? supplierNameById.get(q.supplier) || ""
        : "",
    };
  });
}

async function buildOrderHistory(
  pb: Awaited<ReturnType<typeof getAdminPocketBase>>,
  target: { description: string },
  supplierNameById: Map<string, string>,
): Promise<ItemIntelOrderRow[]> {
  const filter = buildPbContainsOR("description", target.description);
  if (!filter) return [];
  const candRows = await safeGetList<{
    id: string; description: string; cost_price: number; selling_price: number;
    quantity: number; item_status: string; supplier: string; updated: string; order: string;
    expand?: { order?: { order_number: string; company?: string } };
  }>(pb, "order_items", {
    filter,
    expand: "order",
    fields: "id,description,cost_price,selling_price,quantity,item_status,supplier,updated,order,expand.order.id,expand.order.order_number,expand.order.company",
    max: 300,
    sort: "-updated",
  });
  const targetTokens = tokenizeIntel(target.description);
const ranked = candRows.items
    .map((o) => ({ o, score: combinedScore(targetTokens, tokenizeIntel(o.description || "")) }))
    .filter((r) => r.score >= 0.5)
    .sort((a, b) => b.score - a.score)
    .slice(0, ITEM_INTEL_LIMITS.recentOrder);
  return ranked.map(({ o, score }) => ({
    score: +score.toFixed(3),
    order_item_id: o.id,
    order_id: o.order,
    order_number: o.expand?.order?.order_number || "",
    description: o.description || "",
    cost_price: o.cost_price || 0,
    selling_price: o.selling_price || 0,
    quantity: o.quantity || 0,
    item_status: o.item_status || "",
    supplier_id: o.supplier || "",
    supplier_name: supplierNameById.get(o.supplier) || o.supplier || "",
    updated: o.updated,
    days_ago: daysAgo(o.updated),
  }));
}

// ─── Summary ─────────────────────────────────────────────────────────

function composeSummary(input: {
  matches: ItemIntelStockRow[];
  supplierHistory: ItemIntelSupplierRow[];
  recent_quote: ItemIntelQuoteRow[];
  recent_order: ItemIntelOrderRow[];
  price_list: ItemIntelPriceListRow[];
}): string {
  const bits: string[] = [];
  const topStock = input.matches[0];
  if (topStock && topStock.qty > 0) {
    bits.push(`in stock ${topStock.qty} (${topStock.supplier_name || "—"}, cost R${topStock.cost_price.toFixed(2)})`);
  } else if (topStock) {
    bits.push(`out of stock (last supplier ${topStock.supplier_name || "—"})`);
  }
  if (input.supplierHistory.length === 1) {
    const s = input.supplierHistory[0];
    bits.push(`bought from ${s.supplier_name} ${s.days_ago}d ago @ R${s.last_cost.toFixed(2)} (×${s.times_bought})`);
  } else if (input.supplierHistory.length > 1) {
    bits.push(`bought from ${input.supplierHistory.length} suppliers — top: ${input.supplierHistory[0].supplier_name} R${input.supplierHistory[0].last_cost.toFixed(2)} ${input.supplierHistory[0].days_ago}d ago`);
  }
  const lq = input.recent_quote[0];
  if (lq) bits.push(`last quoted R${lq.selling_price.toFixed(2)} ${lq.days_ago}d ago (${lq.quote_number})`);
  const lo = input.recent_order[0];
  if (lo) bits.push(`last order ${lo.days_ago}d ago (${lo.order_number}, ${lo.item_status})`);
  if (input.price_list.length > 0) bits.push(`on price list (${input.price_list.length})`);
  return bits.join(" · ") || "No history yet for this item.";
}

// ─── Public entry points ─────────────────────────────────────────────

/**
 * Compute and write the Item Intel payload for one quote_item or
 * order_item. Collection is the PB collection name (e.g.
 * `"quote_items"`). The intel is written to `<collection>.ai_item_insights`.
 *
 * `write: false` runs the whole algorithm without persisting — use
 * for the live preview path.
 */
export async function populateItemIntel(
  itemId: string,
  collection: "quote_items" | "order_items",
  options: { write?: boolean } = {},
): Promise<ItemIntel> {
  const write = options.write !== false;
  const pb = await getAdminPocketBase();

  const target = await pb.collection(collection).getOne<{
    id: string; sku: string; description: string; quantity: number;
    supplier: string;
  }>(itemId, { fields: "id,sku,description,quantity,supplier" });

  const supplierNameById = await loadSuppliersById(pb);
  const generated_at = new Date().toISOString();

  const [stockRaw, price_list, recent_quote, recent_order] = await Promise.all([
    buildStock(pb, target, supplierNameById),
    buildPriceList(pb, target),
    buildQuoteHistory(pb, target, supplierNameById),
    buildOrderHistory(pb, target, supplierNameById),
  ]);

  const supplier_history = buildLastSupplierPrice(stockRaw.purchaseHistory);

  const item: ItemIntelTarget = {
    id: itemId,
    collection,
    description: target.description || "",
    sku: target.sku || "",
    quantity: target.quantity || 0,
    supplier: target.supplier || "",
    supplier_name: target.supplier
      ? supplierNameById.get(target.supplier) || ""
      : "",
  };

  const summary = composeSummary({
    matches: stockRaw.matches,
    supplierHistory: supplier_history,
    recent_quote,
    recent_order,
    price_list,
  });

  const intel: ItemIntel = {
    item,
    summary,
    generated_at,
    stock_list: stockRaw.matches,
    supplier_history,
    price_list,
    recent_quote,
    recent_order,
  };

  if (write) {
    await pb.collection(collection).update(itemId, { ai_item_insights: intel });
  }

  return intel;
}

/**
 * Populate Item Intel for every active line on a quote or order.
 * Parallel-safe within one parent; the caller controls cross-parent
 * batching to avoid hammering PB.
 */
export async function populateIntelForParent(
  parentId: string,
  collection: "quote_items" | "order_items",
  parentCollection: "quotes" | "orders",
  options: { write?: boolean } = {},
): Promise<{ parent_id: string; total: number; populated: number; no_match: number }> {
  const pb = await getAdminPocketBase();
  const parentField = parentCollection === "quotes" ? "quote" : "order";
  const items = await pb.collection(collection).getFullList<{ id: string }>({
    filter: `${parentField} = "${parentId}" && (moved_to_quote = null || moved_to_quote = "")`,
    fields: "id",
  });
  const results = await Promise.all(
    items.map((it) => populateItemIntel(it.id, collection, options).then(
      (intel) => ({
        id: it.id,
        found: intel.stock_list.length > 0 || intel.price_list.length > 0 ||
               intel.recent_quote.length > 0 || intel.recent_order.length > 0 ||
               intel.supplier_history.length > 0,
      }),
      () => ({ id: it.id, found: false }),
    )),
  );
  return {
    parent_id: parentId,
    total: items.length,
    populated: results.filter((r) => r.found).length,
    no_match: results.filter((r) => !r.found).length,
  };
}