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marketplace-personalisation

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Personalisation and recommendation systems for a two-sided trust marketplace built on AWS Personalize — event tracking, dataset and schema design, two-sided matching, cold start, feedback loops, bias control, recipe selection, serving-time re-ranking, observability, and a diagnostic playbook for existing systems. Trigger when designing, building, debugging, reviewing, or improving such a system — and even when the user does not explicitly mention "AWS Personalize" but is working on recommendations, ranking, search, homepage personalisation, or anything that matches seekers and providers across a trust-based catalog.

skills/.experimental/marketplace-personalisation/SKILL.md

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# Marketplace Engineering Two-Sided Personalisation Best Practices

Comprehensive guide for designing, building and improving personalisation and recommendation
systems in two-sided trust marketplaces on AWS Personalize. Contains 49 rules across 9
categories, ordered by cascade impact on the personalisation lifecycle, plus two playbooks
for planning a new system from scratch and diagnosing an existing one.

## When to Apply

Reference this skill when:

- Designing the event schema and tracking for a new recommender system
- Choosing an AWS Personalize recipe (USER_PERSONALIZATION_v2, SIMS, PERSONALIZED_RANKING_v2)
- Writing or reviewing candidate-generation and re-ranking code for marketplace search or homefeed
- Handling cold start for new providers, new seekers, or new catalog regions