Present one queued review question and log the result to the MCP study server.
npx skills add https://github.com/joseph0926/study-all --skill review-joseph0926
Please help me install this Agent Skill. Skill: review Source: https://github.com/joseph0926/study-all/tree/main/.codex/skills/review Command: npx skills add https://github.com/joseph0926/study-all --skill review-joseph0926
This skill automates the process of drawing one review question from the learning backlog and recording the result in the MCP study server, enabling efficient spaced-review workflows without manual tracking.
Start a review session by invoking review <skill-name> [topic] to fetch the next question and begin scoring.
High-intent search queries and answers about installing and using this skill.
To automate fetching review questions from a learning backlog, this skill uses a queue-driven mechanism to pull the next unfixed problem and present it for answering. It integrates with the MCP study server to log results without manual tracking.
Queue-based spaced review is a practice method that sequentially presents backlog questions. This skill tracks study progress by automatically recording question outcomes and scores to the MCP study server for analytics and mastery measurement.
To start a review session for a specific topic, invoke the command review <skill-name> [topic]. This fetches the next available question from the queue and begins the scoring process within your learning workflow.
Yes, you can target specific learning topics during a study review session by providing optional topic context. This allows you to focus the queue-driven practice on specific areas and measure your mastery over time.
Yes, an MCP server integration is required to log quiz results. The skill uses review.recordResult to send scores and outcomes directly to the MCP study server, enabling automated progress tracking and analytics across your skills.
A limitation of this queue-based review system is that it strictly presents one question at a time from the backlog. It relies entirely on MCP server availability for logging scores and requires specific context resolution to fetch the queue.
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