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headless-intelligent-search无头智能搜索

Agent Skill

headless-intelligent-search 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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3,127

周安装

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:headless-intelligent-search(无头智能搜索)
来源仓库:https://github.com/vtex/skills
仓库路径:skills/headless-intelligent-search
安装命令:
npx skills add https://github.com/vtex/skills --skill headless-intelligent-search
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/vtex/skills --skill headless-intelligent-search

简介

headless-intelligent-search 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 适用于智能搜索算法、语义匹配或知识库构建等无头架构下的信息检索需求。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 了解具体调用方式。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Intelligent Search API Integration

When this skill applies

Use this skill when implementing product search, category browsing, autocomplete, or faceted filtering in a headless VTEX storefront.

  • Building a search results page with product listings
  • Implementing faceted navigation (category, brand, price, color filters)
  • Adding autocomplete suggestions to a search input
  • Wiring up search analytics events for Intelligent Search ranking

Do not use this skill for:

Decision rules

  • Call Intelligent Search directly from the frontend — it is the ONE exception to the "everything through BFF" rule. It is fully public and requires no authentication.
  • Do NOT proxy Intelligent Search through the BFF unless you have a specific need (e.g., server-side rendering). Proxying adds latency on a high-frequency operation.
  • Always use the API's sort parameter and facet paths for filtering and sorting — never re-sort or re-filter results client-side.
  • Always include page and locale parameters in every search request.
  • When paginating beyond the first page, always reuse the operator and fuzzy values returned by the API from the first page — the API decides these values dynamically based on the search query.
  • Always send analytics events to the Intelligent Search Events API — without them, search ranking degrades over time.

Search endpoints overview:

EndpointMethodPurpose
/product_search/{facets}GETSearch products by query and/or facets
/facets/{facets}GETGet available filters for a query
/autocomplete_suggestionsGETGet term and product suggestions while typing
/top_searchesGETGet the 10 most popular search terms
/correction_searchGETGet spelling correction for a misspelled term
/search_suggestionsGETGet suggested terms similar to the search term
/banners/{facets}GETGet banners configured for a query

Facet combination rules:

  • Same facet type → OR (union): Selecting "Red" and "Blue" for color returns products matching either color
  • Different facet types → AND (intersection): Selecting "Red" color and "Nike" brand returns only red Nike products

Hard constraints

Constraint: MUST send analytics events to Intelligent Search Events API

Every headless search implementation MUST send analytics events to the Intelligent Search Events API - Headless. At minimum, send search impression events when results are displayed and click events when a product is selected from search results.

Why this matters

Intelligent Search uses machine learning to rank results based on user behavior. Without analytics events, the search engine has no behavioral data and cannot personalize or optimize results. Over time, search quality degrades compared to stores that send events. Additionally, VTEX Admin search analytics dashboards will show no data.

Detection

If a search implementation renders results from Intelligent Search but has no calls to sp.vtex.com/event-api or the Intelligent Search Events API → STOP immediately. Analytics events must be implemented alongside search.

Correct

// search-analytics.ts — sends events to Intelligent Search Events API
const ACCOUNT_NAME = "mystore";
const EVENTS_URL = `https://sp.vtex.com/event-api/v1/${ACCOUNT_NAME}/event`;

interface SearchEvent {
  type: "search.query" | "search.click" | "search.add_to_cart";
  text: string;
  misspelled: boolean;
  match: number;
  operator: string;
  locale: string;
  agent: string;
  url: string;
  products?: Array<{ productId: string; position: number }>;
}

export async function sendSearchEvent(event: SearchEvent): Promise<void> {
  try {
    await fetch(EVENTS_URL, {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify(event),
      keepalive: true, // ensures event is sent even during navigation
    });
  } catch (error) {
    // Analytics failures should not break the UI
    console.warn("Failed to send search event:", error);
  }
}

// Usage: call after rendering search results
function onSearchResultsRendered(query: string, products: Product[]): void {
  sendSearchEvent({
    type: "search.query",
    text: query,
    misspelled: false,
    match: products.length,
    operator: "and",
    locale: "en-US",
    agent: "my-headless-store",
    url: window.location.href,
    products: products.map((p, i) => ({
      productId: p.productId,
      position: i + 1,
    })),
  });
}

Wrong

// Search works but NO analytics events are sent — search ranking degrades
async function searchProducts(query: string): Promise<Product[]> {
  const response = await fetch(
    `https://mystore.vtexcommercestable.com.br/api/io/_v/api/intelligent-search/product_search/?query=${query}&locale=en-US`
  );
  const data = await response.json();
  return data.products;
  // Missing: no call to sendSearchEvent() — Intelligent Search cannot learn
}

Constraint: MUST persist operator and fuzzy values across pagination

When paginating search results beyond the first page, you MUST reuse the operator and fuzzy values returned by the API in the first page response. The first request should send these as null, but subsequent pages must use the values from the initial response.

Why this matters

The Intelligent Search API dynamically determines the best operator and fuzzy values based on the query and available results. Using fixed values (like always operator: "or" or fuzzy: "0") or forgetting to pass them on subsequent pages causes inconsistent results — page 2 may show products that don't match the criteria from page 1, or may miss valid results. This is a common source of poor search experience but is not well-documented by VTEX.

Detection

If pagination implementation does not store and reuse operator/fuzzy from the first page response → STOP immediately. Subsequent pages will return inconsistent results.

Correct

// Properly manages operator/fuzzy across pagination
interface SearchState {
  query: string;
  page: number;
  count: number;
  locale: string;
  facets?: string;
  operator: string | null; // null for first page, then persisted
  fuzzy: string | null;    // null for first page, then persisted
}

async function searchProducts(state: SearchState): Promise<SearchResponse> {
  const { query, page, count, locale, facets = "", operator, fuzzy } = state;

  const params = new URLSearchParams({
    query,
    locale,
    page: String(page),
    count: String(count),
  });

  // Only add operator/fuzzy if this is not the first page
  if (operator !== null) params.set("operator", operator);
  if (fuzzy !== null) params.set("fuzzy", fuzzy);

  const baseUrl = `https://${ACCOUNT}.vtexcommercestable.com.br`;
  const facetPath = facets ? `/${facets}` : "";
  const url = `${baseUrl}/api/io/_v/api/intelligent-search/product_search${facetPath}?${params}`;

  const response = await fetch(url);
  const data = await response.json();

  // Store operator/fuzzy from response for next page
  if (page === 0) {
    state.operator = data.operator;
    state.fuzzy = data.fuzzy;
  }

  return data;
}

// Usage: first page
const state: SearchState = {
  query: "running shoes",
  page: 0,
  count: 24,
  locale: "en-US",
  operator: null, // API will decide
  fuzzy: null,    // API will decide
};

const firstPage = await searchProducts(state);

// Usage: subsequent pages
state.page = 1;
const secondPage = await searchProducts(state); // reuses operator/fuzzy

Wrong

// Using fixed operator/fuzzy values — causes bad results
async function searchProducts(query: string, page: number): Promise<SearchResponse> {
  const params = new URLSearchParams({
    query,
    locale: "en-US",
    page: String(page),
    count: "24",
    operator: "or", // WRONG: fixed value instead of API-provided
    fuzzy: "0",     // WRONG: fixed value instead of API-provided
  });

  const response = await fetch(
    `https://mystore.vtexcommercestable.com.br/api/io/_v/api/intelligent-search/product_search/?${params}`
  );
  return response.json();
}

// Or forgetting operator/fuzzy entirely on subsequent pages
async function searchProductsPage2(query: string): Promise<SearchResponse> {
  const params = new URLSearchParams({
    query,
    locale: "en-US",
    page: "1", // WRONG: no operator/fuzzy from first page
    count: "24",
  });
  // ...
}

Constraint: Do NOT unnecessarily proxy Intelligent Search through BFF

Intelligent Search API requests SHOULD be made directly from the frontend. Do not route search traffic through the BFF unless you have a specific need (e.g., server-side rendering, adding custom business logic).

Why this matters

Intelligent Search is a public API that does not require authentication. Adding a BFF proxy layer introduces an additional network hop, increases latency on every search operation, adds server cost, and prevents the CDN from caching responses efficiently. Search queries are high-frequency operations — even 50ms of added latency impacts conversion.

Detection

If all Intelligent Search calls go through a BFF endpoint instead of directly to VTEX → note this to the developer. It is not a security issue but a performance concern. If there is no justification (like SSR), recommend direct frontend calls.

Correct

// Frontend — calls Intelligent Search directly (no BFF needed)
const VTEX_SEARCH_BASE = `https://${ACCOUNT}.vtexcommercestable.com.br/api/io/_v/api/intelligent-search`;

export async function getAutocomplete(term: string, locale: string): Promise<AutocompleteResponse> {
  const params = new URLSearchParams({ query: term, locale });
  const response = await fetch(`${VTEX_SEARCH_BASE}/autocomplete_suggestions?${params}`);
  return response.json();
}

export async function getTopSearches(locale: string): Promise<TopSearchesResponse> {
  const params = new URLSearchParams({ locale });
  const response = await fetch(`${VTEX_SEARCH_BASE}/top_searches?${params}`);
  return response.json();
}

export async function getFacets(facetPath: string, query: string, locale: string): Promise<FacetsResponse> {
  const params = new URLSearchParams({ query, locale });
  const response = await fetch(`${VTEX_SEARCH_BASE}/facets/${facetPath}?${params}`);
  return response.json();
}

Wrong

// BFF proxy for Intelligent Search — unnecessary overhead
// server/routes/search.ts
router.get("/api/bff/search", async (req, res) => {
  const { query, from, to, locale } = req.query;
  // This just forwards to VTEX with no added value
  const response = await fetch(
    `https://mystore.vtexcommercestable.com.br/api/io/_v/api/intelligent-search/product_search/?query=${query}&from=${from}&to=${to}&locale=${locale}`
  );
  const data = await response.json();
  res.json(data); // Added latency for no benefit
});

Preferred pattern

Data flow for Intelligent Search in a headless storefront:

Frontend (Browser)
    │
    ├── GET /api/io/_v/api/intelligent-search/product_search/...
    │   └── Returns: products, pagination info, operator, fuzzy
    │
    ├── GET /api/io/_v/api/intelligent-search/facets/...
    │   └── Returns: available filters with counts
    │
    ├── GET /api/io/_v/api/intelligent-search/autocomplete_suggestions?query=...
    │   └── Returns: suggested terms + suggested products
    │
    └── POST https://sp.vtex.com/event-api/v1/{account}/event
        └── Sends: search impressions, clicks, add-to-cart events

Typed search API client for all endpoints:

// lib/intelligent-search-client.ts
const ACCOUNT = "mystore";
const ENVIRONMENT = "vtexcommercestable";
const BASE_URL = `https://${ACCOUNT}.${ENVIRONMENT}.com.br/api/io/_v/api/intelligent-search`;

interface ProductSearchParams {
  query?: string;
  page: number;
  count?: number;
  locale: string;
  facets?: string;
  sort?: "price:asc" | "price:desc" | "orders:desc" | "name:asc" | "name:desc" | "release:desc" | "discount:desc";
  hideUnavailableItems?: boolean;
  operator?: string | null;
  fuzzy?: string | null;
  // Optional parameters
  simulationBehavior?: "default" | "skip" | "only1P";
}

interface ProductSearchResponse {
  products: Product[];
  recordsFiltered: number;
  // Pagination info
  pagination: {
    count: number;
    current: { index: number };
    before: Array<{ index: number }>;
    after: Array<{ index: number }>;
    perPage: number;
    next: { index: number } | null;
    previous: { index: number } | null;
    first: { index: number };
    last: { index: number };
  };
  // Search metadata to persist for next pages
  operator: string;
  fuzzy: string;
  // Spelling correction info
  correction?: {
    misspelled: boolean;
    text: string;
    correction: string;
  };
  // Search behavior
  translated: boolean;
  locale: string;
  query: string;
}

export async function productSearch(params: ProductSearchParams): Promise<ProductSearchResponse> {
  const { facets = "", operator, fuzzy, ...queryParams } = params;
  const searchParams = new URLSearchParams();

  if (queryParams.query) searchParams.set("query", queryParams.query);
  searchParams.set("page", String(queryParams.page));
  searchParams.set("locale", queryParams.locale);
  if (queryParams.count) searchParams.set("count", String(queryParams.count));
  if (queryParams.sort) searchParams.set("sort", queryParams.sort);
  if (queryParams.hideUnavailableItems) searchParams.set("hideUnavailableItems", "true");
  if (queryParams.simulationBehavior) searchParams.set("simulationBehavior", queryParams.simulationBehavior);

  // Only add operator/fuzzy if not null (i.e., not first page)
  if (operator !== null && operator !== undefined) searchParams.set("operator", operator);
  if (fuzzy !== null && fuzzy !== undefined) searchParams.set("fuzzy", fuzzy);

  const facetPath = facets ? `/${facets}` : "";
  const url = `${BASE_URL}/product_search${facetPath}?${searchParams}`;

  const response = await fetch(url);
  if (!response.ok) {
    throw new Error(`Search failed: ${response.status}`);
  }
  return response.json();
}

Response structure notes:

  • operator and fuzzy: Must be stored from the first page and reused on subsequent pages. Also critical for analytics events.
  • pagination: Contains rich pagination metadata including available pages before/after current
  • correction.misspelled: Boolean indicating if the search term is misspelled. Must be sent accurately in analytics events.
  • recordsFiltered: Total number of results matching the search (across all pages)
  • products: Array of products for the current page only

Faceted navigation helper:

// lib/facets.ts
export async function getFacets(
  facetPath: string,
  query: string,
  locale: string
): Promise<FacetsResponse> {
  const params = new URLSearchParams({ query, locale });
  const url = `${BASE_URL}/facets/${facetPath}?${params}`;

  const response = await fetch(url);
  if (!response.ok) {
    throw new Error(`Facets fetch failed: ${response.status}`);
  }
  return response.json();
}

// Build facet path from selected filters
export function buildFacetPath(selectedFilters: Record<string, string[]>): string {
  const parts: string[] = [];
  for (const [key, values] of Object.entries(selectedFilters)) {
    for (const value of values) {
      parts.push(`${key}/${value}`);
    }
  }
  return parts.join("/");
}

Debounced autocomplete for search inputs:

// lib/autocomplete.ts
export function createDebouncedAutocomplete(delayMs: number = 300) {
  let timeoutId: ReturnType<typeof setTimeout> | null = null;

  return function debouncedAutocomplete(
    query: string,
    locale: string,
    callback: (suggestions: AutocompleteResponse) => void
  ): void {
    if (timeoutId) clearTimeout(timeoutId);

    if (query.length < 2) {
      callback({ searches: [] });
      return;
    }

    timeoutId = setTimeout(async () => {
      const params = new URLSearchParams({ query, locale });
      const response = await fetch(`${BASE_URL}/autocomplete_suggestions?${params}`);
      const suggestions = await response.json();
      callback(suggestions);
    }, delayMs);
  };
}

Full search orchestration with analytics:

// search-page.ts — framework-agnostic search orchestration
import { productSearch } from "./lib/intelligent-search-client";
import { getFacets, buildFacetPath } from "./lib/facets";
import { createDebouncedAutocomplete } from "./lib/autocomplete";
import { sendSearchEvent } from "./search-analytics";

interface SearchState {
  query: string;
  page: number;
  count: number;
  locale: string;
  selectedFilters: Record<string, string[]>;
  operator: string | null;
  fuzzy: string | null;
  results: ProductSearchResponse | null;
  facets: FacetsResponse | null;
}

const state: SearchState = {
  query: "",
  page: 0,
  count: 24,
  locale: "en-US",
  selectedFilters: {},
  operator: null, // API decides on first page
  fuzzy: null,    // API decides on first page
  results: null,
  facets: null,
};

async function executeSearch(): Promise<void> {
  const facetPath = buildFacetPath(state.selectedFilters);

  const [searchResults, facetResults] = await Promise.all([
    productSearch({
      query: state.query,
      page: state.page,
      count: state.count,
      locale: state.locale,
      facets: facetPath,
      operator: state.operator,
      fuzzy: state.fuzzy,
    }),
    getFacets(facetPath, state.query, state.locale),
  ]);

  // Store operator/fuzzy from first page for subsequent pages
  if (state.page === 0) {
    state.operator = searchResults.operator;
    state.fuzzy = searchResults.fuzzy;
  }

  state.results = searchResults;
  state.facets = facetResults;

  // Send analytics event after results are rendered
  sendSearchEvent({
    type: "search.query",
    text: state.query,
    misspelled: searchResults.correction?.misspelled ?? false,
    match: searchResults.recordsFiltered,
    operator: searchResults.operator,
    locale: state.locale,
    agent: "my-headless-store",
    url: window.location.href,
    products: searchResults.products.map((p, i) => ({
      productId: p.productId,
      position: state.page * searchResults.products.length + i + 1,
    })),
  });
}

// Handle product click from search results — send click event
function onProductClick(productId: string, position: number): void {
  sendSearchEvent({
    type: "search.click",
    text: state.query,
    misspelled: false,
    match: state.results?.recordsFiltered ?? 0,
    operator: state.results?.operator ?? "and",
    locale: state.locale,
    agent: "my-headless-store",
    url: window.location.href,
    products: [{ productId, position }],
  });
}

// Handle page change
function goToPage(newPage: number): void {
  state.page = newPage;
  executeSearch(); // reuses operator/fuzzy from first page
}

// Handle new search (reset pagination state)
function newSearch(query: string): void {
  state.query = query;
  state.page = 0;
  state.operator = null; // reset for new search
  state.fuzzy = null;    // reset for new search
  executeSearch();
}

Common failure modes

  • Not tracking correction.misspelled and operator fields for analytics: The API returns correction.misspelled (boolean indicating if the term is misspelled) and operator fields that must be sent correctly in analytics events. These values are critical for the Intelligent Search machine learning to understand search quality and user behavior. const response = await productSearch({query: "red nike shoes", page: 0, locale: "en-US"}); // Extract values from API response const isMisspelled = response.correction?.misspelled?? false; const operatorUsed = response.operator; // "and" or "or" // CRITICAL: Send these exact values to analytics sendSearchEvent({type: "search.query", text: response.query, misspelled: isMisspelled, // Must match API's correction.misspelled operator: operatorUsed, // Must match API's operator value match: response.recordsFiltered, locale: state.locale, agent: "my-headless-store", url: window.location.href, products: response.products.map((p, i) => ({productId: p.productId, position: i + 1,})),});
  • Not sending the locale parameter: Without locale, Intelligent Search may return results in the wrong language or fail to apply locale-specific relevance rules. Multi-language stores will display mixed-language results. Always include locale in every request. // Always include locale in search parameters const params = new URLSearchParams({query: "shoes", locale: "en-US", // Required for correct language processing page: "0", count: "24",});
  • Using fixed operator/fuzzy values or forgetting to persist them: Setting fixed values like operator: "or" or fuzzy: "0" for all requests, or not passing them at all on subsequent pages. The API dynamically determines these values on the first page — you must store and reuse them for pagination. // Store operator/fuzzy from first page, reuse on subsequent pages let searchState = {operator: null, fuzzy: null}; const firstPage = await productSearch({query: "shoes", page: 0, count: 24, locale: "en-US"}); searchState.operator = firstPage.operator; // Store from API response searchState.fuzzy = firstPage.fuzzy; // Page 2 reuses these values const secondPage = await productSearch({query: "shoes", page: 1, count: 24, locale: "en-US", operator: searchState.operator, // Reuse from first page fuzzy: searchState.fuzzy,});
  • Assuming /product_search returns facets: The /product_search endpoint returns only products and pagination info. To get available filters, you must call the separate /facets endpoint. Make parallel requests if you need both. // Fetch products and facets in parallel const [products, filters] = await Promise.all([productSearch({query: "shoes", page: 0, locale: "en-US"}), getFacets("", "shoes", "en-US"), // Separate call for filters]);
  • Not using hideUnavailableItems when appropriate: By default, the API may return out-of-stock products. For most storefronts, set hideUnavailableItems: true to filter them out at the API level rather than client-side. const response = await productSearch({query: "shoes", page: 0, locale: "en-US", hideUnavailableItems: true, // Filter out-of-stock products});
  • Rebuilding search ranking logic client-side: Fetching results and then re-sorting or re-filtering them in the frontend discards Intelligent Search's ranking intelligence. Client-side filtering only works on the current page, not the full catalog. Use the API's sort parameter and facet paths. // Use API-level sorting — don't re-sort in the frontend const results = await productSearch({query: "shirt", sort: "price:asc", // API handles sorting across entire result set locale: "en-US", from: 0, to: 23, facets: "category-1/clothing/color/red", // API handles filtering across entire catalog});

Review checklist

  • Is Intelligent Search called directly from the frontend (not unnecessarily routed through BFF)?
  • Does every search request include page and locale parameters?
  • Are operator and fuzzy values stored from the first page and reused on subsequent pages?
  • Are correction.misspelled and operator from the API response sent correctly in analytics events?
  • Are analytics events sent to sp.vtex.com/event-api after search results render?
  • Are click events sent when a user selects a product from search results?
  • Is sorting done via the API's sort parameter rather than client-side re-sorting?
  • Is filtering done via facet paths rather than client-side filtering?
  • Is autocomplete debounced to avoid excessive API calls?
  • Are filters fetched from the /facets endpoint (not assumed to come from /product_search)?
  • Is hideUnavailableItems set to true for storefronts that should hide out-of-stock products?

Reference

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.06%
按下载量换算358

Claude

31.22%
按下载量换算319

Cursor

17.18%
按下载量换算176

Gemini CLI

9.41%
按下载量换算96

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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