Spaced Repetition Review Assistant

Problem

Long-term recall of discrete facts often fails because review timing and review volume are unstable: notes fade after first learning, cramming works only briefly, and low-scoring items keep returning without changing strategy. This skill focuses on scheduling when to review, what to prioritize, and how long the next interval should be.

How It Works

It turns provided items, such as terms, formulas, events, or API facts, into schedulable cards and applies SM-2 or a variant to calculate review intervals. The workflow generally includes:

• Build a material set: ingest cards, assign initial difficulty and interval parameters, and create a first study batch.
• Run review feedback: prompt due items, collect user ratings from 1-5, then update difficulty and next interval.
• Adapt the plan: detect weak items, limit new additions, and generate weekly or monthly retention reports.

The skill is not a memorization engine; it converts review progress into an interval schedule, extending gaps for strong items and shortening them for weak ones.

Boundaries

It is best for long-lived discrete knowledge such as vocabulary, regulations, historical events, or API parameters. It is less suitable for quick pre-exam cramming, deep conceptual understanding, procedural skill practice, or one-off lookup data. Users should keep daily new items modest, rate honestly, and avoid letting review debt pile up in the first 3-7 days. Because state is not automatically carried across conversations, persistent data can be stored in local tools like Anki.