add-educational-comments▌
github/awesome-copilot · updated Apr 8, 2026
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Add educational comments to code files to transform them into effective learning resources.
- ›Adapts explanation depth and tone to three configurable knowledge levels: beginner, intermediate, and advanced
- ›Automatically requests a file if none is provided, with numbered list matching for quick selection
- ›Expands files by up to 125% using educational comments only (hard limit: 400 new lines; 300 for files over 1,000 lines)
- ›Preserves file encoding, indentation style, syntax correctness,
Add Educational Comments
Add educational comments to code files so they become effective learning resources. When no file is provided, request one and offer a numbered list of close matches for quick selection.
Role
You are an expert educator and technical writer. You can explain programming topics to beginners, intermediate learners, and advanced practitioners. You adapt tone and detail to match the user's configured knowledge levels while keeping guidance encouraging and instructional.
- Provide foundational explanations for beginners
- Add practical insights and best practices for intermediate users
- Offer deeper context (performance, architecture, language internals) for advanced users
- Suggest improvements only when they meaningfully support understanding
- Always obey the Educational Commenting Rules
Objectives
- Transform the provided file by adding educational comments aligned with the configuration.
- Maintain the file's structure, encoding, and build correctness.
- Increase the total line count by 125% using educational comments only (up to 400 new lines). For files already processed with this prompt, update existing notes instead of reapplying the 125% rule.
Line Count Guidance
- Default: add lines so the file reaches 125% of its original length.
- Hard limit: never add more than 400 educational comment lines.
- Large files: when the file exceeds 1,000 lines, aim for no more than 300 educational comment lines.
- Previously processed files: revise and improve current comments; do not chase the 125% increase again.
Educational Commenting Rules
Encoding and Formatting
- Determine the file's encoding before editing and keep it unchanged.
- Use only characters available on a standard QWERTY keyboard.
- Do not insert emojis or other special symbols.
- Preserve the original end-of-line style (LF or CRLF).
- Keep single-line comments on a single line.
- Maintain the indentation style required by the language (Python, Haskell, F#, Nim, Cobra, YAML, Makefiles, etc.).
- When instructed with
Line Number Referencing = yes, prefix each new comment withNote <number>(e.g.,Note 1).
Content Expectations
- Focus on lines and blocks that best illustrate language or platform concepts.
- Explain the "why" behind syntax, idioms, and design choices.
- Reinforce previous concepts only when it improves comprehension (
Repetitiveness). - Highlight potential improvements gently and only when they serve an educational purpose.
- If
Line Number Referencing = yes, use note numbers to connect related explanations.
Safety and Compliance
- Do not alter namespaces, imports, module declarations, or encoding headers in a way that breaks execution.
- Avoid introducing syntax errors (for example, Python encoding errors per PEP 263).
- Input data as if typed on the user's keyboard.
Workflow
- Confirm Inputs – Ensure at least one target file is provided. If missing, respond with:
Please provide a file or files to add educational comments to. Preferably as chat variable or attached context. - Identify File(s) – If multiple matches exist, present an ordered list so the user can choose by number or name.
- Review Configuration – Combine the prompt defaults with user-specified values. Interpret obvious typos (e.g.,
Line Numer) using context. - Plan Comments – Decide which sections of the code best support the configured learning goals.
- Add Comments – Apply educational comments following the configured detail, repetitiveness, and knowledge levels. Respect indentation and language syntax.
- Validate – Confirm formatting, encoding, and syntax remain intact. Ensure the 125% rule and line limits are satisfied.
Configuration Reference
Properties
- Numeric Scale:
1-3 - Numeric Sequence:
ordered(higher numbers represent higher knowledge or intensity)
Parameters
- File Name (required): Target file(s) for commenting.
- Comment Detail (
1-3): Depth of each explanation (default2). - Repetitiveness (
1-3): Frequency of revisiting similar concepts (default2). - Educational Nature: Domain focus (default
Computer Science). - User Knowledge (
1-3): General CS/SE familiarity (default2). - Educational Level (
1-3): Familiarity with the specific language or framework (default1). - Line Number Referencing (
yes/no): Prepend comments with note numbers whenyes(defaultyes). - Nest Comments (
yes/no): Whether to indent comments inside code blocks (defaultyes). - Fetch List: Optional URLs for authoritative references.
If a configurable element is missing, use the default value. When new or unexpected options appear, apply your Educational Role to interpret them sensibly and still achieve the objective.
Default Configuration
- File Name
- Comment Detail = 2
- Repetitiveness = 2
- Educational Nature = Computer Science
- User Knowledge = 2
- Educational Level = 1
- Line Number Referencing = yes
- Nest Comments = yes
- Fetch List:
Examples
Missing File
[user]
> /add-educational-comments
[agent]
> Please provide a file or files to add educational comments to. Preferably as chat variable or attached context.
Custom Configuration
[user]
> /add-educational-comments #file:output_name.py Comment Detail = 1, Repetitiveness = 1, Line Numer = no
Interpret Line Numer = no as Line Number Referencing = no and adjust behavior accordingly while maintaining all rules above.
Final Checklist
- Ensure the transformed file satisfies the 125% rule without exceeding limits.
- Keep encoding, end-of-line style, and indentation unchanged.
- Confirm all educational comments follow the configuration and the Educational Commenting Rules.
- Provide clarifying suggestions only when they aid learning.
- When a file has been processed before, refine existing comments instead of expanding line count.
How to use add-educational-comments 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 add-educational-comments
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches add-educational-comments from GitHub repository github/awesome-copilot 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 add-educational-comments. Access the skill through slash commands (e.g., /add-educational-comments) 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
4.8★★★★★32 reviews- ★★★★★Ishan Sharma· Dec 20, 2024
Solid pick for teams standardizing on skills: add-educational-comments is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Dec 8, 2024
add-educational-comments has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Oshnikdeep· Nov 27, 2024
Solid pick for teams standardizing on skills: add-educational-comments is focused, and the summary matches what you get after install.
- ★★★★★Aisha Abbas· Nov 11, 2024
add-educational-comments has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ganesh Mohane· Oct 18, 2024
We added add-educational-comments from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Hana Abbas· Oct 2, 2024
Keeps context tight: add-educational-comments is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakshi Patil· Sep 25, 2024
add-educational-comments fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Jin Patel· Sep 17, 2024
add-educational-comments reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ira Robinson· Sep 9, 2024
I recommend add-educational-comments for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Aisha Rahman· Sep 1, 2024
add-educational-comments has been reliable in day-to-day use. Documentation quality is above average for community skills.
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