Add learning category schema

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Goal

Add a learning category schema for apps that understand study and skill-building preferences.

This should help Memact turn learning activity into user-readable Wiki entries that users can approve, edit, reject, or delete.

Context examples

Learning apps may know things like:

• topics being studied
• preferred explanation style
• difficulty level
• repeated mistakes or weak areas
• completed lessons
• study goals
• preferred pace
• preferred format such as text, video, quiz, or project

Work to do

• Define useful context fields for the learning category
• Add example raw app context dumps
• Add normalized context examples
• Add user-facing Wiki entry templates
• Mark sensitive or risky fields clearly
• Suggest category-level permissions apps should request
• Add tests for safe context shaping

Important product rule

Learning context should help personalization without labeling users permanently by weak areas or temporary confusion.

Acceptance criteria

• Schema separates current learning goals from stable preferences
• Raw app input examples exist
• Normalized output examples exist
• Wiki entry examples are human-readable
• Tests cover at least one valid and one overconfident inference case

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Maintainer note for SSoC26 contributors:

Please comment before starting so work does not get duplicated. Keep the first PR small and focused.

For category schemas, apps should propose context; users control what becomes accepted memory. Prefer user-readable summaries over raw personal data, avoid sensitive trait inference, and do not write fake certainty.

Before opening a PR, read MEMACT.md and make sure your schema includes examples, Wiki entry outputs, permission suggestions, and at least basic tests.