marketplace-search-recsys-planning

name

marketplace-search-recsys-planning

description

Search and recommendation system planning for a two-sided trust marketplace built on OpenSearch — user-intent framing, product-surface architecture, index design, query understanding, retrieval strategy, ranking, search-plus-recs blending, measurement, and a dashboard-and-alerting layer for ongoing decision making. Triggers on tasks involving marketplace search, homefeeds, ranking, relevance tuning, OpenSearch query DSL, analyzers, synonyms, golden sets, NDCG, A/B testing, or diagnosing an existing retrieval system. Use this skill BEFORE marketplace-personalisation when planning new work; hand off when the diagnosed bottleneck is personalisation-specific.

Marketplace Engineering Two-Sided Search and Recsys Planning Best Practices

Comprehensive planning, design and diagnostic guide for search and recommendation systems in two-sided trust marketplaces. Covers OpenSearch index, query and ranking patterns, the methodology for planning retrieval work, the handoff points to recommendation-specific tooling, and the instrumentation and dashboard layer that turns measurement into ongoing decision making. Contains 57 rules across 10 categories ordered by cascade impact, plus two playbooks (plan a new system from scratch, diagnose an existing one) and explicit living-artefact conventions (decisions log, golden set, gotchas).

When to Apply

Reference this skill when:

• Planning a new marketplace retrieval project from scratch
• Reviewing an existing retrieval system that feels stale, unfair, or unpersonalised
• Designing the OpenSearch index mapping, analyzers, or query DSL
• Choosing retrieval primitives per product surface (search, recs, hybrid, curated)
• Deciding which search quality metrics to track and dashboard
• Running the weekly search-quality review ritual
• Diagnosing a silent regression in ranking, coverage, or zero-result rate
• Deciding when a retrieval problem is actually a personalisation problem

This skill is the precursor to marketplace-personalisation. Start here for planning and search work; hand off to the personalisation skill when the diagnosed bottleneck is impression tracking, feedback-loop bias, or AWS Personalize-specific design.