Technical Design for Marketplace Search Feature

Problem/Feature Description

An e-commerce startup is building a product search feature for their multi-vendor marketplace. They have a React web frontend, need a dedicated search microservice, a product catalog database, and want to integrate with an external AI ranking API to improve result quality.

Your task is to produce a technical plan for this feature.

Output Specification

Produce planning artifacts in specs/002-marketplace-search/.

Input Files

The following files are provided as inputs. Extract them before beginning.

=============== FILE: specs/002-marketplace-search/spec.md ===============

Feature Spec: Marketplace Search

Branch: 002-marketplace-search | Date: 2026-01-20 | Status: specified

User Stories

US1: Search products

As a shopper, I want to search for products by keyword so that I can quickly find what I'm looking for.

Acceptance Scenarios:

• Given a search query of "red shoes", when submitted, then products matching the keyword are returned ranked by relevance
• Given a search with no results, when submitted, then an empty result set with a helpful message is returned

US2: Filter and sort results

As a shopper, I want to filter search results by category and price range so that I can narrow down my options.

Acceptance Scenarios:

• Given search results for "shoes", when filtered by price < $50, then only products under $50 appear
• Given search results, when sorted by rating, then results appear in descending rating order

US3: AI-enhanced ranking

As a marketplace operator, I want search results to be ranked using an AI service so that more relevant products appear higher.

Acceptance Scenarios:

• Given a product search, when the AI ranking service is available, then results are re-ranked by the AI score
• Given the AI ranking service is unavailable, when a search is performed, then results fall back to keyword relevance ranking

Functional Requirements

• FR-001: The system MUST accept text search queries and return matching products within 500ms at up to 100 concurrent users
• FR-002: The system MUST support filtering by category, price range, and rating
• FR-003: The system MUST integrate with an external AI ranking API to re-rank results when available
• FR-004: The system MUST fall back to keyword relevance ranking if the external AI service is unavailable
• FR-005: Search queries and results MUST be logged for analytics purposes
• FR-006: The system MUST expose a REST API endpoint for the frontend to consume

Success Criteria

• SC-001: Search API responds within 500ms at 100 concurrent users
• SC-002: AI ranking is applied when the external service responds within 200ms
• SC-003: Fallback to keyword ranking occurs within 50ms when AI service is unavailable
• SC-004: All search queries are captured in the analytics log with user session ID

=============== FILE: .specify/context.json =============== { "projectName": "marketplace-platform", "version": "1.0.0" }