Beginner Progression Score

Beginner Progression Score MCP Connector for Claude

A+

Track skill advancement and estimate time to mastery.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides tools to quantify learning progress for beginners. Use calculate_current_progression to determine a normalized advancement score, recommend_next_skills to identify the most effective next steps in a skill tree, and estimate_time_to_next_level to project milestones based on practice habits. It also includes analyze_practice_efficiency to evaluate how environmental factors and instruction quality impact learning speed.

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4 tools expose this connector's capabilities to your AI agent.

estimate_time_to_next_level

Predicts how much more time is needed to reach the next milestone

analyze_practice_efficiency

Evaluates how effectively a user is using their practice time based on environmental factors

calculate_current_progression

Determines the user's current overall progression score

recommend_next_skills

Identifies which skills the user should focus on to maximize progression

See how to talk to your AI agent using Beginner Progression Score.

What is my current progression score if I have practiced for 20 hours, mastered 'basic_stance' and 'footwork', have a natural ability of 1.2, and an instruction factor of 1.1?

Your current progression score is 15.5 with a momentum of 1.8.

Based on my current score of 45, how many weeks until I reach a score of 60 if I practice 5 hours per week with a natural ability of 1.0?

You are estimated to reach the target score in 4 weeks with a 90% confidence interval.

How efficient was my 10-hour practice session if the conditions difficulty was 0.8 and instruction quality was 0.9?

Your efficiency rating is 0.85. To improve, try maintaining high instruction quality even when conditions are less challenging.

The score is a weighted metric combining cumulative practice hours, achieved skills, natural ability, and the quality of instruction received.

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