📄️ Learning Overview
Overview of MPLP Learning Feedback Duties. Explains the purpose of converting execution history into structured learning samples for model training and evaluation.
📄️ Learning Collection Points
Specification of Learning Collection Points in MPLP. Defines triggers and moments in the agent lifecycle (intent, execution, governance) for capturing learning samples.
📄️ Learning Feedback
Learning and feedback mechanisms for MPLP including sample collection, PII anonymization, implicit/explicit feedback capture, and training data export for RLHF/SFT.
📄️ Learning Invariants
Normative invariants for MPLP Learning Samples. Defines validation rules for sample structure, required fields, and family-specific constraints to ensure data quality.
📄️ Learning Sample Schema
Reference for MPLP Learning Sample Schemas. Details the Core, Intent, and Delta schemas for structuring learning data from agent executions.