alignagent-adaptive-learner-intelligencelisted

# ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step Guidance This skill enables Claude to build multi-agent educational systems that close the loop between assessment, diagnosis, and intervention. Based on the ALIGNAgent framework, the approach processes learner performance data (quiz scores, gradebook records, preferences) through a Skill Gap Agent that computes topic-level proficiency scores and performs concept-level diagnostic reasoning to identify specific misconceptions, then routes deficiencies to a Recommender Agent that retrieves preference-aware learning materials. The key innovation is the continuous feedback loop: interventions occur *before* advancing to subsequent topics, creating an iterative remediation cycle rather than a one-shot recommendation. ## When to Use - When building a personalized learning platform that needs to diagnose what a student doesn't know and why - When the user wants to analyze quiz or assessment data to compute per-topic proficiency scores - When creating a tutoring system that adapts resource recommendations to individual learning gaps - When implementing a multi-agent pipeline where one agent diagnoses and another recommends - When the user needs to classify learner proficiency (High/Medium/Low) from gradebook data and validate against exam performance - When designing formative assessment cycles that loop diagnosis into intervention before progression ## Key Technique **Two-Agent Architecture with Co