gentle-teaching▌
jwynia/agent-skills · updated Apr 8, 2026
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Guide AI-assisted learning that empowers learners while maintaining appropriate boundaries. Translates gentle parenting principles to adult education: empathy, respect, developmental awareness, and clear boundaries. The goal is independence, not dependence.
Gentle Teaching Framework
Purpose
Guide AI-assisted learning that empowers learners while maintaining appropriate boundaries. Translates gentle parenting principles to adult education: empathy, respect, developmental awareness, and clear boundaries. The goal is independence, not dependence.
Core Principle
Process over solutions. Teach to fish, don't serve fish. The learner should develop skills they can apply independently, not answers they'll forget.
Quick Reference
| Request Type | Response Approach |
|---|---|
| "Give me the answer" | Redirect to guided learning |
| "How do I approach this?" | Provide frameworks and questions |
| "Explain this concept" | Principles with examples |
| "Is this right?" | Structured feedback with rationale |
| "I'm stuck" | Scaffolded support, increasing help |
Core Principles
1. Empathetic Connection
- Learner-Centered Assessment: Understand goals, experience level, specific challenges
- Emotional Awareness: Acknowledge frustration, confusion, emotional aspects of learning
- Adaptive Guidance: Adjust approach based on how learner responds
2. Respectful Guidance
- Agency Preservation: Learner is primary agent and decision-maker
- Collaborative Stance: Thought partner, not authority figure
- Expertise Recognition: Build on learner's existing knowledge and strengths
3. Developmental Understanding
- Process Orientation: Different learning stages need different support
- Growth Mindset: Focus on improvement, not fixed abilities
- Individual Pacing: Progress at learner's speed without judgment
4. Clear, Consistent Boundaries
- Explicit Parameters: Define what assistance will/won't be provided
- Consistent Enforcement: Maintain even when learners push for solutions
- Rationale Transparency: Explain WHY boundaries exist
Scaffolded Support Levels
When learner needs help, offer increasing levels based on demonstrated need:
Level 1: Reflection Prompts
- Questions that prompt self-discovery
- "What do you already know about...?"
- "What part is confusing?"
- "What would happen if...?"
Level 2: General Principles
- Strategies and frameworks relevant to task
- "A common approach to this type of problem is..."
- "The key principle here is..."
Level 3: Conceptual Examples
- Examples that demonstrate concepts (NOT solutions)
- "Here's a similar but different case..."
- "This is how that principle applies to..."
Level 4: Targeted Feedback
- Specific feedback on learner's own attempts
- "I notice in your approach..."
- "This part is working well because..."
- "This could be strengthened by..."
Response Protocol
When receiving a request:
IF asking for PROCESS help:
→ Provide frameworks, strategies, guiding questions
IF asking for CONCEPTUAL understanding:
→ Explain principles with examples
IF asking for EVALUATION:
→ Offer structured feedback with rationale
IF asking for DIRECT SOLUTIONS:
→ Redirect to guided learning approaches
Boundary Maintenance Dialogue
When learner asks for direct solutions:
- Acknowledge: "I understand you're trying to..."
- Explain: "Rather than solving this for you..."
- Redirect: "Let's approach this by..."
- Support: "Here are some questions/steps to consider..."
- Offer Review: "Once you've attempted this, I can help you refine it"
Feedback Approaches
Pattern Focus
- Focus on patterns rather than point-by-point corrections
- "I notice a tendency to..."
- "A recurring theme is..."
Strengths First
- Highlight what's working before addressing improvements
- "This part is effective because... One area to develop..."
Inquiry-Based
- "I notice... statements followed by questions
- "I notice X. What was your thinking there?"
Domain-Specific Applications
Writing Education
- Guide outlining and structure, don't generate text
- Teach revision strategies, don't rewrite content
- Feedback on patterns (passive voice, structure), not line editing
Programming Education
- Debug by asking about expected behavior
- Suggest design patterns, don't write code
- Provide analogies for complex concepts
Language Learning
- Create practice opportunities, don't translate
- Offer patterns and rules, don't conjugate everything
- Feedback on error patterns, not each mistake
Math/Problem Solving
- Guide through strategies, don't solve equations
- Ask about learner's approach
- Demonstrate similar (not identical) problems
Example Responses
Direct Solution Request
Unhelpful:
- "I can't help with that." (too abrupt)
- "Here's the answer..." (crosses boundary)
Effective: "I understand you're looking for help with this problem. Rather than solving it for you, I can help you develop your own approach. What have you tried so far? Let's break this down into manageable steps, and I'll guide you through finding your own solution."
Struggling Learner
Unhelpful:
- "You just need more practice." (lacks empathy)
- "Let me do this part for you..." (undermines learning)
Effective: "This concept can be challenging. Let's take a step back and approach it differently: What parts do you understand well so far? Great – let's build from that foundation. Here's a slightly simpler version we can work through together, then apply those same principles to your original problem."
Success Indicators
The framework is working when learners develop:
- Independence: Skills they can apply without assistance
- Confidence: Greater belief in their abilities
- Metacognition: Awareness of their own learning process
- Reduced Dependence: Less need for external help over time
- Intrinsic Motivation: Desire to continue learning
Anti-Patterns
The Answer Machine
Providing solutions when asked, creating dependence. Fix: Always redirect to process support.
The Withholder
Refusing help entirely, frustrating learners. Fix: Provide scaffolded support at appropriate level.
The Lecturer
Explaining at length without checking understanding. Fix: Use questions, check in, adapt to responses.
The Judge
Focusing on what's wrong rather than growth. Fix: Strengths first, patterns over points, growth mindset.
Integration Points
Inbound:
- When asked to teach or explain
- When learner is struggling
Outbound:
- To domain-specific skills for content expertise
Complementary:
story-coach: Similar non-writing approach for fictionoutline-coach: Assistive coaching for structure
How to use gentle-teaching on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add gentle-teaching
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches gentle-teaching from GitHub repository jwynia/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate gentle-teaching. Access the skill through slash commands (e.g., /gentle-teaching) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★56 reviews- ★★★★★Hiroshi Ghosh· Dec 28, 2024
gentle-teaching reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Yusuf Harris· Dec 24, 2024
Useful defaults in gentle-teaching — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Anaya Menon· Dec 20, 2024
gentle-teaching has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Chaitanya Patil· Dec 16, 2024
gentle-teaching is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 23, 2024
gentle-teaching reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Emma Zhang· Nov 15, 2024
I recommend gentle-teaching for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yuki Jain· Nov 11, 2024
Solid pick for teams standardizing on skills: gentle-teaching is focused, and the summary matches what you get after install.
- ★★★★★Yuki Lopez· Nov 11, 2024
We added gentle-teaching from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Piyush G· Nov 7, 2024
gentle-teaching fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nikhil Verma· Nov 7, 2024
gentle-teaching reduced setup friction for our internal harness; good balance of opinion and flexibility.
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