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Agent Skill · 研究检索

commerce-api-gateway(commerce API gateway 搜索)

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

commerce-api-gateway 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 58,252。

总安装 419周安装 18GitHub Stars 19下载 147核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:commerce-api-gateway(commerce API gateway 搜索)
来源仓库:https://github.com/finsilabs/awesome-ecommerce-skills
仓库路径:skills/commerce-api-gateway
安装命令:
npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill commerce-api-gateway
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/finsilabs/awesome-ecommerce-skills --skill commerce-api-gateway

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

commerce-api-gateway 用于辅助 API 网关设计、接口文档生成和服务集成说明。适用于梳理 endpoint、生成 OpenAPI 草稿、检查字段命名及整理错误码等场景。

通过安装命令 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill commerce-api-gateway 从 GitHub 仓库安装使用。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。

来源仓库内路径:skills/commerce-api-gateway

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill com…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

commerce-api-gateway 怎么安装?

在终端执行 npx skills add https://github.com/finsilabs/awesome-ecommerce-skills --skill commerce-api-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

commerce-api-gateway 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

commerce-api-gateway 需要什么权限?

权限级别是需要联网。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。

commerce-api-gateway 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

commerce-api-gateway 用的人多吗?

公开数据是累计安装 419 次,近一周安装 18 次,下载 147 次,GitHub 19 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

commerce-api-gateway 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
commerce-api-gateway

commerce API gateway 搜索 · 本页

41919需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Commerce API Gateway

Overview

An API gateway sits between storefront clients and the set of backend commerce services, providing a single entry point for authentication, rate limiting, caching, and request routing. In composable commerce architectures, the gateway aggregates APIs from disparate services (catalog, cart, search, CMS) so the frontend makes one or a few calls rather than dozens. This skill covers building a GraphQL Federation gateway with Apollo Router, a REST aggregation BFF, and applying cross-cutting concerns (auth, rate limiting, observability) at the gateway layer.

When to Use This Skill

  • When your storefront makes 10+ API calls per page load from different services
  • When you need to enforce authentication and authorization consistently across all commerce APIs
  • When different teams own different services and you need a contract between the frontend and backend
  • When you want to apply rate limiting, circuit breakers, or caching without modifying each service
  • When you need a single GraphQL schema that spans catalog, inventory, CMS, and personalization data

Prerequisites & Platform Notes

This skill is written for custom/headless storefronts (Node.js, Python, or similar backend). The code examples use TypeScript/Node.js and can be adapted to any stack.

Shopify: Shopify Hydrogen is Shopify's headless framework. MACH/composable patterns apply when using Shopify as the commerce backend with a custom frontend, or when mixing Shopify with other best-of-breed services. WooCommerce: WooCommerce can serve as a headless backend via its REST API and WPGraphQL. These patterns apply when decoupling the frontend from WordPress. Magento: Magento's GraphQL API and PWA Studio support headless architectures. These composable patterns apply to Magento as a backend service in a MACH stack.

You'll need:

  • Node.js 18+ (or adapt to your backend language)
  • Redis for caching/queues

Core Instructions

  1. Set up Apollo Router for GraphQL Federation Apollo Federation composes multiple GraphQL subgraphs into a unified supergraph. Each service owns a slice of the schema. # Install Apollo Router (the high-performance Rust gateway) curl -sSL https://router.apollo.dev/download/nix/latest | sh # Install Rover CLI for schema management npm install -g @apollo/rover Define the supergraph config: # supergraph.yaml federation_version: =2.5.0 subgraphs: catalog: routing_url: http://catalog-service:4001/graphql schema: subgraph_url: http://catalog-service:4001/graphql inventory: routing_url: http://inventory-service:4002/graphql schema: subgraph_url: http://inventory-service:4002/graphql cart: routing_url: http://cart-service:4003/graphql schema: subgraph_url: http://cart-service:4003/graphql Compose and run: rover supergraph compose --config supergraph.yaml > supergraph.graphql./router --supergraph supergraph.graphql --config router.yaml
  2. Define federated subgraph schemas Each service defines its slice of the schema and can extend types owned by other services: # catalog-service/schema.graphql type Query {product(id: ID!): Product products(first: Int, after: String): ProductConnection} type Product @key(fields: "id") {id: ID! name: String! slug: String! description: String price: Money! images: [Image!]!} # inventory-service/schema.graphql — extends Product from catalog type Product @key(fields: "id") @extends {id: ID! @external inventory: InventoryStatus!} type InventoryStatus {available: Boolean! quantity: Int warehouseLocations: [String!]!} The gateway resolves the Product.inventory field by calling the inventory service with the product IDs gathered from the catalog response — automatically, without any client-side orchestration.
  3. Build a REST BFF (Backend-for-Frontend) with Fastify For storefronts that prefer REST over GraphQL: import Fastify from 'fastify'; import {catalogClient} from './services/catalog'; import {inventoryClient} from './services/inventory'; import {cmsClient} from './services/cms'; const app = Fastify({logger: true}); // Composite endpoint for Product Detail Page app.get<{Params: {id: string}}>('/api/pdp/:id', async (request, reply) => {const {id} = request.params; const customerId = request.headers['x-customer-id'] as string | undefined; const [product, inventory, content] = await Promise.allSettled([catalogClient.getProduct(id), inventoryClient.getStock(id), cmsClient.getProductContent(id),]); if (product.status === 'rejected') {return reply.status(404).send({error: 'Product not found'});} return {product: product.value, inventory: inventory.status === 'fulfilled'? inventory.value: {available: true, quantity: null}, content: content.status === 'fulfilled'? content.value: null,};}); // Composite endpoint for Cart Page app.get<{Params: {cartId: string}}>('/api/cart/:cartId', {preHandler: [requireAuth],}, async (request, reply) => {const cart = await cartClient.getCart(request.params.cartId); const productIds = cart.lines.map((l: any) => l.productId); const inventoryMap = await inventoryClient.getBulkStock(productIds); return {...cart, lines: cart.lines.map((line: any) => ({...line, inventory: inventoryMap[line.productId]?? {available: true},})),};}); await app.listen({port: 3000, host: '0.0.0.0'});
  4. Apply authentication at the gateway The gateway validates JWTs and forwards the decoded identity to subgraphs: // middleware/auth.ts import {FastifyRequest, FastifyReply} from 'fastify'; import {verify, JwtPayload} from 'jsonwebtoken'; export async function requireAuth(request: FastifyRequest, reply: FastifyReply) {const token = request.headers.authorization?.replace('Bearer ', ''); if (!token) return reply.status(401).send({error: 'Authentication required'}); try {const payload = verify(token, process.env.JWT_PUBLIC_KEY!, {algorithms: ['RS256']}) as JwtPayload; request.user = {id: payload.sub!, email: payload.email, roles: payload.roles?? []};} catch {return reply.status(401).send({error: 'Invalid token'});}} // Apollo Router auth via coprocessor (Rust plugin alternative) // router.yaml # router.yaml authentication: router: jwt: jwks: - url: https://your-auth-provider/.well-known/jwks.json authorization: require_authentication: false # Allow public queries; subgraphs enforce per-field auth
  5. Implement rate limiting and response caching // Rate limiting with Redis token bucket import {RateLimiterRedis} from 'rate-limiter-flexible'; import Redis from 'ioredis'; const redis = new Redis(process.env.REDIS_URL!); const rateLimiter = new RateLimiterRedis({storeClient: redis, keyPrefix: 'rl_gateway', points: 100, // 100 requests duration: 60, // per 60 seconds blockDuration: 60, // block for 60s when exceeded}); app.addHook('preHandler', async (request, reply) => {const key = request.user?.id?? request.ip; try {await rateLimiter.consume(key);} catch {reply.header('Retry-After', '60'); return reply.status(429).send({error: 'Too many requests'});}}); // Response caching with stale-while-revalidate import {fastifyCaching} from '@fastify/caching'; app.register(fastifyCaching, {privacy: fastifyCaching.privacy.PUBLIC, expiresIn: 60});
  6. Add distributed tracing with OpenTelemetry // tracing.ts — initialize before importing app modules import {NodeSDK} from '@opentelemetry/sdk-node'; import {OTLPTraceExporter} from '@opentelemetry/exporter-trace-otlp-http'; import {HttpInstrumentation} from '@opentelemetry/instrumentation-http'; const sdk = new NodeSDK({serviceName: 'commerce-gateway', traceExporter: new OTLPTraceExporter({url: process.env.OTEL_EXPORTER_OTLP_ENDPOINT}), instrumentations: [new HttpInstrumentation()],}); sdk.start(); // Propagate trace context to downstream services // OpenTelemetry auto-injects W3C traceparent headers into all outgoing HTTP requests

Examples

Apollo Router configuration with caching and CORS

# router.yaml
server:
  listen: 0.0.0.0:4000
  cors:
    origins:
      - https://www.mystore.com
      - https://staging.mystore.com

supergraph:
  listen: 0.0.0.0:4000

traffic_shaping:
  router:
    timeout: 30s
  all:
    timeout: 10s
    retry:
      enabled: true
      min_per_sec: 10
      ttl: 10s
      retry_on_http_statuses: [500, 502, 503]

telemetry:
  tracing:
    otlp:
      endpoint: http://otel-collector:4317
      protocol: grpc

Schema stitching for legacy REST services

import {wrapSchema, RenameTypes, FilterTypes} from '@graphql-tools/wrap';
import {fetch} from 'undici';

// Wrap a legacy REST API as a virtual GraphQL subgraph
const legacyProductSchema = buildSchema(`
  type Query {
    legacyProduct(sku: String!): LegacyProduct
  }
  type LegacyProduct {
    sku: String!
    name: String!
    wholesalePrice: Float!
  }
`);

const legacyProductSubschema = {
  schema: legacyProductSchema,
  executor: async ({document, variables}: any) => {
    const sku = variables.sku;
    const res = await fetch(`${process.env.LEGACY_API_URL}/products/${sku}`);
    const product = await res.json();
    return {data: {legacyProduct: product}};
  },
};

Best Practices

  • Keep the gateway thin — the gateway handles cross-cutting concerns (auth, rate limiting, caching, tracing); business logic belongs in the services
  • Use Apollo Federation for GraphQL — schema stitching works but federation is the standard; it enforces clear ownership and enables schema registry checks in CI
  • Set per-service timeouts — a slow inventory service should not hold up a product page; set independent timeouts for each subgraph and use @defer for non-critical data
  • Cache at the gateway, not the client — use Cache-Control and Fastify/Apollo caching plugins to serve repeated queries from memory; this reduces load on all downstream services
  • Version the gateway API, not the subgraphs — expose /api/v1 and /api/v2 prefixes at the gateway level; individual subgraph schemas evolve independently under federation
  • Use health check endpoints for each subgraph — configure the router to poll /health on each service and remove unhealthy subgraphs from routing automatically
  • Monitor gateway latency as a system-level SLO — the gateway p99 latency is the ceiling on every user interaction; alert when it exceeds your page performance budget

Common Pitfalls

ProblemSolution
N+1 queries when resolving entity referencesUse Apollo Federation's @key and batch-resolving (DataLoader pattern) to fetch all referenced entities in one call per service
Auth token not forwarded to subgraphsConfigure Apollo Router's headers.all propagation to forward Authorization and x-customer-id headers to all subgraphs
Gateway becomes a bottleneck under loadDeploy Apollo Router as a horizontally scaled stateless service behind a load balancer; it has a Rust core and handles thousands of RPS per instance
Subgraph schema conflict blocks deploymentUse rover subgraph check in CI to validate schema changes against the registry before merging
Cross-origin requests blocked from the SPASet CORS origins explicitly to your storefront domains; never use wildcard * on an authenticated gateway

Related Skills

  • @composable-commerce
  • @webhook-architecture
  • @monitoring-alerting-commerce
  • @edge-commerce
  • @load-testing-commerce

平台分布

Codex

33.95%
按下载量换算50

Claude

30.55%
按下载量换算45

Cursor

19.92%
按下载量换算29

Gemini CLI

9.67%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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