home / skills / zeeshan080 / ai-native-robotics / student-language-guide

student-language-guide skill

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This skill helps you tailor student-facing language by simplifying terms, adding analogies, and avoiding internal labels in educational content.

npx playbooks add skill zeeshan080/ai-native-robotics --skill student-language-guide

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: student-language-guide
description: Provide student-facing language rules for educational content. Use when writing lessons, checking language appropriateness, or validating content for students.
allowed-tools: Read
---

# Student Language Guide

## Instructions

When writing student-facing content:

1. Use clear, accessible language
2. Avoid internal jargon and labels
3. Include analogies for complex concepts
4. Match language complexity to layer

## Golden Rules

1. **Never expose internal labels** (L1, L2, etc. to students)
2. **Avoid jargon** without explanation
3. **Use active voice** for instructions
4. **Include analogies** for abstract concepts
5. **Be encouraging** but not condescending

## Language Dos and Don'ts

| DO | DON'T |
|----|-------|
| "In this lesson, you'll learn..." | "This L2 content covers..." |
| "Think of a robot like a..." | "The robot abstraction..." |
| "Try this exercise" | "Execute the following procedure" |
| "You've learned a lot!" | "Basic concepts completed" |

## Reference

See [examples.md](examples.md) for good/bad examples.

Overview

This skill provides student-facing language rules and concrete phrasing guidance for educational content. It helps writers convert technical curriculum and developer-facing notes into clear, age-appropriate lessons that respect learners and avoid internal jargon. Use it to shape tone, phrasing, and examples so materials are accessible and encouraging.

How this skill works

The skill inspects lesson text and flags internal labels, jargon, passive constructions, and phrasing that may sound condescending or too technical. It suggests alternatives, offers analogy prompts for abstract concepts, and recommends complexity adjustments to match the learner layer. Outputs are short, actionable rewrites and rule-based checks.

When to use it

Writing new lessons or exercises for students
Reviewing technical notes to make them student-facing
Validating language complexity for a specified learner level
Preparing in-class scripts, handouts, or assignment prompts
Converting internal documentation into teaching material

Best practices

Start instructions with active voice and second person (you) when appropriate
Remove internal labels (L1, L2, etc.) and replace with descriptive names
Replace jargon with plain terms or provide a simple analogy if needed
Keep sentences short and concrete; aim for one idea per sentence
Use encouraging language that acknowledges effort without patronizing

Example use cases

Turn a developer note: 'This L2 module covers locomotion controllers' into 'In this lesson, you will learn how robots walk and balance.'
Check a worksheet to replace 'Execute the following procedure' with 'Try this step-by-step activity.'
Suggest analogies for teaching sensors, e.g., 'Think of sensors like a robot's senses—eyes and ears that help it understand the world.'
Validate that assessment feedback sounds supportive: 'Nice progress—try the next challenge' instead of 'Basic concepts completed.'
Adjust lesson tone to match beginner, intermediate, or advanced student layers

FAQ

Can this skill rewrite entire lessons automatically?

It provides suggested rewrites and specific phrasing alternatives; authors should review and adapt them to preserve pedagogy and technical accuracy.

How does it decide the appropriate complexity level?

You specify the learner layer or target audience; the skill uses that input to simplify vocabulary, shorten sentences, and suggest analogies suited to that level.