recall

Run interactive recall sessions from concept briefs and prediction logs.

Updated Aug 27, 2026

Search Tags:#recall #learning #spaced-repetition #study-sessions #anki #anki-connect #active-recall

Ready to run

npx skills add https://github.com/vitalwarley/hyprdots --skill recall-vitalwarley

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: recall
Source: https://github.com/vitalwarley/hyprdots/tree/main/claude-global/skills/recall
Command: npx skills add https://github.com/vitalwarley/hyprdots --skill recall-vitalwarley

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns ad-hoc knowledge gaps and failed predictions into focused active-recall practice and durable Anki flashcards so learners can close gaps and retain codebase concepts over time.

Core Features & Use Cases

Interactive, back-and-forth recall sessions that source questions from concept briefs and the prediction log and adapt selection with spaced-repetition priorities.
Multiple modes: automatic recent-gap selection, session-limited topical questions, topic-specific full review, and a review-mode that computes recall performance metrics.
Anki export via AnkiConnect that creates Basic-model cards with source and code references; logs session results to docs/learning/prediction-log.md for tracking and scheduling.
Use case: a developer rehearses recent misunderstandings about a repository pattern, reinforces learning with targeted questions, and exports new cards to an Anki deck for long-term retention.

Quick Start

Use the recall skill to run a short interactive session that presents 3–5 questions from concept briefs and prediction gaps and then offer to export any new cards to Anki.

Frequently Asked Questions about recall

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert learning gaps into Anki flashcards?▼

To convert learning gaps into Anki flashcards, this Skill reads concept briefs and prediction logs to run interactive active-recall sessions, then connects to AnkiConnect at localhost:8765 to export new Basic-model cards with source references.

How does active-recall practice work with spaced-repetition sessions?▼

Active-recall practice with spaced-repetition sessions works by prompting you to answer questions sourced from concept briefs and prediction logs, recording your results, and adapting question selection based on recall performance metrics.

Can I use AnkiConnect to export active-recall study session results?▼

Yes, you can use AnkiConnect to export active-recall study session results by connecting to localhost:8765, which creates Basic-model Anki cards containing source and code references from your completed recall sessions.

Do I need a prediction log to run short study sessions?▼

You need docs/learning/prediction-log.md and docs/learning/concepts files to run short study sessions, as the Skill reads these sources to select and present questions for your interactive active-recall practice.

What is the best way to review codebase concepts using spaced-repetition?▼

The best way to review codebase concepts using spaced-repetition is running topic-focused review sessions that compute recall performance metrics, log results to prediction-log.md, and schedule future practice based on your recorded misunderstandings.

Why does AnkiConnect fail to create flashcards from study sessions?▼

AnkiConnect fails to create flashcards from study sessions when the localhost:8765 connection is unavailable, as the Skill requires a running AnkiConnect instance to export Basic-model cards with source and code references.