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    Lecture Notes to Active Recall Generator

    2

    Transforms lecture notes and transcripts into evidence-based active recall questions and flashcards.

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    Lecture Notes to Active Recall Generator

    Lecture Notes to Active Recall Generator

    Example session with this skill installed

    I am uploading my notes from a 200-level Microeconomics lecture on Elasticity. Create 10 flashcards and a question bank focused on the Midpoint Method and Cross-Price Elasticity.

    • Read your context and instructions
    • Compiled the lecture notes to

    I have analyzed your Microeconomics notes on Elasticity. I identified 4 core concepts, flagged one missing variable in the Income Elasticity formula, and generated the requested study materials.

    Active Recall Study Pack

    1. Key Concept Inventory

    ConceptSource-grounded explanationConnection/importanceStatus
    Price ElasticityMeasure of responsiveness of quantity demanded to a change in price.Central to total revenue analysis.Supported
    Midpoint MethodFormula used to calculate percentage changes using the average of initial and final values.Avoids different results depending on direction of change.Supported
    Cross-Price ElasticityMeasures how the quantity demanded of one good responds to a change in the price of another.Distinguishes between substitutes and complements.Supported

    2. Question Bank

    • ID 001 (Medium): Why is the Midpoint Method preferred over the standard percentage change formula in elasticity?

    Answer: It provides a consistent elasticity value regardless of whether price increases or decreases by using the average as the base.

    ID 002 (Hard): If the Cross-Price Elasticity between Good A and Good B is -1.5, what is the relationship between them?

    Answer: They are complements. A negative value indicates that as the price of one rises, demand for the other falls.

    3. Flashcards

    IDFrontBackTopic/tagTypeDifficulty
    FC-01Define the formula for the Midpoint Method.(Q2-Q1)/[(Q2+Q1)/2] / (P2-P1)/[(P2+P1)/2]ElasticityFormulaHard
    FC-02Cross-Price Elasticity > 0 implies?The goods are substitutes.ElasticityConceptMedium

    4. Clarification Flags

    TopicIssueQuestion to resolveImpact
    Income ElasticityThe formula in the notes is missing the denominator for quantity.Is the denominator the initial quantity or the midpoint?Blocks formula application.

    Next steps

    1. Resolve the flagged formula ambiguity using your textbook.
    2. Export the flashcard table to a CSV for Anki import.
    3. Review the Question Bank in 24 hours to test initial retention.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Standard summaries often fail to test true understanding, leading to the illusion of competence. This skill transforms raw lecture notes, transcripts, and slides into a structured study system centered on active recall and retrieval practice.

    What it does

    • Concept inventorying extracts key definitions, formulas, and theories directly from your notes while mapping their interconnections.
    • Multi-tier question generation builds recall, explanation, comparison, and synthesis questions to test different cognitive levels.
    • Flashcard construction produces independently understandable cards formatted for Q&A, cloze, or Anki-compatible CSVs.
    • Application practice creates scenarios that require applying concepts to new contexts based on the source material.
    • Clarification flagging identifies ambiguous terminology, missing variables in formulas, or contradictions within the provided text.

    How it works

    1. Analyze source by providing lecture notes, transcripts, or slide content along with the course level and exam type.
    2. Review inventory as the agent maps the core concepts and flags any fragments that need human clarification.
    3. Generate pack including a question bank, formatted flashcards, and a model answer key.
    4. Follow the study plan using the suggested spaced-repetition intervals and recall tracker.

    Frameworks & tools

    The skill produces structured text and Markdown tables. It can generate data formatted for Anki, Quizlet, or spreadsheet imports using standard CSV delimiters.

    Why this beats prompting it yourself

    Generic prompts often hallucinate missing information or create repetitive, surface-level questions. This skill specifically identifies gaps in your notes and varies question types to ensure you aren't just memorizing phrasing but actually understanding the mechanics.

    Use cases

    • Exam preparation to convert a semester of messy transcripts into a structured retrieval bank.
    • Note auditing to find missing steps in complex processes or undefined acronyms before a test.
    • Anki deck creation for generating high-volume, high-quality cards without manual data entry.

    Known limitations

    Does not perform external fact-checking unless requested. Result quality depends heavily on the clarity of the input notes. Cannot guarantee specific questions will appear on official exams.

    Requires legible input text. Does not provide external fact-checking by default. Output volume is limited by the depth of the provided source material to avoid repetition.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    What's inside

    Frequently Asked Questions

    The skill works best with typed lecture notes, raw transcripts, and text-based slide content; simply upload your text, specify the course level, and the agent will begin the conceptual inventory.

    Unlike generic prompts that might miss nuances, this skill identifies logical gaps and contradictions in your notes while generating tiered questions—ranging from simple recall to complex synthesis—to prevent the 'illusion of competence.'

    Yes, the skill can export your study materials as Anki-compatible CSVs, Quizlet-ready lists, or structured Markdown tables for easy integration into your existing study workflow.

    You receive the full agent configuration and logic designed for this specific workflow, along with templates for question banks and a guide on using the suggested spaced-repetition intervals.

    The agent focuses on transforming your provided content and does not cross-reference external databases for fact-checking; if your notes contain an error, the agent will reflect that unless it identifies a logical contradiction.

    This skill is designed to be compatible with most major LLMs that support document analysis and structured data output, including ChatGPT, Claude, and specialized AI study environments.

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