user-profiling

Personalize learning paths by collecting user profile data through a five-question survey covering experience level, ROS familiarity, hardware access, learning goals, and language preference. Store responses in PostgreSQL and generate tailored module recommendations, content difficulty levels, and hardware-aware resources automatically.

Yes. This Skill persists profiles in Neon PostgreSQL with efficient queries, supporting collect, retrieve, update, and analyze operations. Profiles include a computed hash for caching, enabling fast lookups and updates without re-collecting survey data.

Validation enforces required fields and checks that responses match valid values for each question. The Skill reports errors and completeness status, rejecting incomplete or malformed submissions before they reach the database.

The Skill generates persona classification, recommended content difficulty, module suggestions tailored to goals and experience, estimated learning duration, and hardware-aware resource paths—all structured for downstream personalization and decision-making.

Yes. The Skill supports profile updates to reflect changing goals or experience, and provides deletion capabilities to enforce privacy controls. Data is used strictly for personalization and can be removed on request.

Yes. This Skill is designed for robotics education, with hardware-access awareness (simulation vs. physical) and ROS familiarity as core survey fields. It tailors recommendations and resource paths based on robotics-specific learning goals and platform constraints.