Which AI agents can I use with the lb teaching toolkit?

This skill is compatible with any text-based AI agent. For users who want to normalize language profiles, an optional Python 3.11+ script is provided, though no external runtimes are required for the core pedagogical generation.

How does this prevent the AI from changing my scientific or technical data?

Unlike generic prompting, this skill uses a strict schema designed to preserve technical integrity, ensuring that complex equations, code, and citations remain intact while generating new instructional content. It specifically solves the problem of "hallucinated" facts that often occur when standard models attempt to simplify scientific material.

What exactly is included in the purchase package?

You will receive the core skill logic for generating worked examples and assessments, an optional Python script for language normalization, and a pedagogical audit framework to help you align new materials with your original learning objectives.

Can I use this to adapt my English-language lectures for international students?

Absolutely. The toolkit includes a multilingual support feature that localizes student-facing explanations and prose while keeping the underlying technical formulas and code in their original, accurate format.

What is the typical workflow for generating a teaching package?

Simply provide your raw lecture notes and target audience details to your AI agent. The skill then analyzes your content to identify pedagogical gaps and outputs a suite of classroom-ready artifacts like rubrics and retrieval questions.

Quiz & Rubric Builder for Lectures

Example session with this skill installed

Add worked examples, a 5-question retrieval quiz, and a grading rubric to my lecture notes on "Photosynthesis and Carbon Fixation" for a high school biology audience. Output in English.

Read your context and instructions
Compiled the quiz & rubric

I have processed the photosynthesis lecture notes and generated the teaching inserts, student assessment, and instructor key. The technical descriptions of the Calvin Cycle and light-dependent reactions were preserved while adding high-school-level analogies and scaffolding.

Teaching Artifacts: Photosynthesis

Artifact	Content Summary
teaching_inserts.json	Includes a worked example of calculating ATP yield and a misconception check on "dark reactions."
student_assessment.md	5 retrieval questions covering photon absorption, water photolysis, and RuBisCO function.
instructor_key.md	Detailed answers for the quiz with specific point allocations for partial credit.
alignment_matrix.md	Maps each question to the corresponding section of the lecture notes and Bloom's taxonomy level.
pedagogical_review.md	Self-audit confirming readability for a 10th-grade audience and retention of all chemical formulas.

Worked Example: The Water-Splitting Step

Problem: A plant is exposed to light. Explain what happens to the water molecule.
Step 1: Light hits Chlorophyll in Thylakoids.
Step 2: Energy strips electrons from H2O.
Step 3: Water breaks into Oxygen (released), Protons (used for gradient), and Electrons (used in the chain).

Next steps

Review the instructor_key.md to ensure the grading weights match your classroom standards.
Export the student_assessment.md content into your Learning Management System (LMS).
Check the pedagogical_review.md for any identified gaps in the retrieval questions.

teaching_inserts.json

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

About this skill

Give the lecture something students can do

Quiz & Rubric Builder for Lectures turns existing notes into practical teaching materials: worked examples, retrieval questions, misconception checks, separate instructor answers and grading criteria.

Use it when the explanation is already written but the lesson still needs practice, assessment and a clear way to evaluate student work.

Keep student work and instructor answers separate

The workflow prepares student-facing tasks and an instructor key as distinct artifacts. Rubrics describe what earns credit, and alignment notes connect tasks to the intended learning outcomes.

Ask for a worked calculation, a short explanation question or a diagnostic task that reveals a specific misconception. The result should fit the lecture's audience and source material rather than introduce unsupported scientific claims merely to make the questions more elaborate.

Adapt without changing the technical meaning

English is the default. Request another language explicitly for questions, answers and rubric descriptions. Formulas, code and source identifiers retain their technical meaning; translations and numerical answers still need review.

Start from the material you already teach

Provide the lecture notes, student level and learning goals. Request the number and type of activities you need. Review the answer key and scoring criteria before using the assessment with students.

For a lecture written from sources, use University Lecture Writer. For coordinated planning, writing, exercises, figures and Word documents, choose AI Lecture Builder Suite.

The core workflow runs as text in a compatible agent without a required local runtime. Python is only needed for the optional helper. This product does not publish automatically to an LMS or certify the scientific accuracy of your lecture.

How to use

Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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Quiz & Rubric Builder for Lectures