# Beginner Progression Score AI Agent Connect > Beginner Progression Score MCP gives your AI client the ability to quantify how fast you are actually learning. It calculates your current advancement, predicts when you will hit your next milestone, and identifies which specific skills you should focus on next to stay efficient. ## Overview - **Category:** productivity - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_zoUG1bHnX3QnpYSqLL9RwWEY77H6Thd7miIOnJa6/ai-agent-connect - **Tags:** learning, progression, skill-tracking, metrics, coaching ## Description Stop guessing if your practice sessions are actually working. This MCP turns raw learning data into actionable metrics that your AI agent can interpret. You can feed your practice hours, mastered skills, and even environmental factors into your client to get a clear picture of your trajectory. It calculates a normalized score for your current progress and uses your specific habits to project exactly how much more time you need to reach your next goal. If you feel like you're stalling, the MCP analyzes your practice efficiency to see if external factors or instruction quality are slowing you down. It's a way to move from vague feelings of improvement to hard numbers that guide your next move. ## Tools ### estimate_time_to_next_level This tool predicts your timeline for reaching the next milestone. It uses your current practice habits to project future progress. ### analyze_practice_efficiency This tool evaluates how well you use your practice time. It looks at how things like instruction quality and environment affect your learning speed. ### calculate_current_progression This tool calculates your current overall advancement score. It provides a normalized number representing your total progress. ### recommend_next_skills This tool identifies the most effective skills to learn next. It looks at your current progress to suggest the best path through a skill tree. ## Prompt Examples **Prompt:** ``` 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? ``` **Response:** ``` Your current progression score is 15.5 with a momentum of 1.8. ``` **Prompt:** ``` 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? ``` **Response:** ``` You are estimated to reach the target score in 4 weeks with a 90% confidence interval. ``` **Prompt:** ``` How efficient was my 10-hour practice session if the conditions difficulty was 0.8 and instruction quality was 0.9? ``` **Response:** ``` Your efficiency rating is 0.85. To improve, try maintaining high instruction quality even when conditions are less challenging. ``` ## Capabilities ### Progress Quantification Your agent uses this to turn practice hours and mastered skills into a single advancement score. ### Milestone Projection Your agent calculates the remaining time needed to reach specific skill levels. ### Skill Pathing Your agent suggests the most logical next skills to learn based on your current tree. ### Efficiency Auditing Your agent checks how environmental factors and instruction quality impact your learning speed. ## Use Cases ### Athletic Training Track how specific drills and coaching quality affect your progression toward a new skill level. ### Software Skill Acquisition Measure how quickly you are moving through a programming language roadmap. ### Musical Mastery Estimate how many weeks of practice are required to master a specific piece or technique. ### Language Learning Analyze if your study environment is helping or hindering your vocabulary retention. ## Benefits - Converts practice habits into predictable timelines. - Identifies bottlenecks in learning efficiency. - Provides a mathematical basis for skill advancement. - Removes guesswork from deciding which skill to learn next. ## How It Works Connect the MCP to your client and start feeding it your practice data. 1. Connect the MCP to Claude, Cursor, or Windsurf via Vinkius. 2. Provide your practice data like hours, mastered skills, and ability factors. 3. Ask your AI client to calculate your score or predict your next milestone. 4. Use the efficiency analysis to adjust your practice habits. ## Frequently Asked Questions **How do I connect this MCP to my AI client?** You connect once through the Vinkius platform. After that, the MCP is ready to use in any compatible client like Claude or Cursor. **What data do I need to provide for a progression score?** You'll need to provide details like practice hours, specific skills mastered, natural ability levels, and instruction factors. **Can this MCP predict exactly when I will finish a course?** It provides an estimate based on your current practice habits and milestones, often including a confidence interval. **Does this work with any AI model?** It works with any MCP-compatible client. It does not depend on a specific model version. **How does it measure practice efficiency?** It evaluates your practice time against environmental factors and the quality of instruction you receive. **How is the progression score calculated?** The score is a weighted metric combining cumulative practice hours, achieved skills, natural ability, and the quality of instruction received. **Can I get specific skill recommendations?** Yes, the `recommend_next_skills` tool analyzes your current skill set against a difficulty map to suggest the most logical next milestones. **How accurate are the time estimates?** Estimates are projections based on your current momentum, average weekly practice volume, and natural ability, provided with a confidence interval.