Self-Explanatory-Code-Commenting
Self-Explanatory-Code-Commenting是一款code方向的AI技能,核心价值是Guidelines for GitHub Copilot to write comments to achieve self-explanatory code with less comments,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Guidelines for GitHub Copilot to write comments to achieve self-explanatory code with less comments. Examples are in JavaScript but it should work on any language that has comments.
mkdir -p ./skills/self-explanatory-code-commenting && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/self-explanatory-code-commenting/SKILL.md -o ./skills/self-explanatory-code-commenting/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Self-explanatory Code Commenting Instructions
Core Principle
**Write code that speaks for itself. Comment only when necessary to explain WHY, not WHAT.**
We do not need comments most of the time.
Commenting Guidelines
❌ AVOID These Comment Types
**Obvious Comments**
// Bad: States the obvious
let counter = 0; // Initialize counter to zero
counter++; // Increment counter by one**Redundant Comments**
// Bad: Comment repeats the code
function getUserName() {
return user.name; // Return the user's name
}**Outdated Comments**
// Bad: Comment doesn't match the code
// Calculate tax at 5% rate
const tax = price * 0.08; // Actually 8%✅ WRITE These Comment Types
**Complex Business Logic**
// Good: Explains WHY this specific calculation
// Apply progressive tax brackets: 10% up to 10k, 20% above
const tax = calculateProgressiveTax(income, [0.10, 0.20], [10000]);**Non-obvious Algorithms**
// Good: Explains the algorithm choice
// Using Floyd-Warshall for all-pairs shortest paths
// because we need distances between all nodes
for (let k = 0; k < vertices; k++) {
for (let i = 0; i < vertices; i++) {
for (let j = 0; j < vertices; j++) {
// ... implementation
}
}
}**Regex Patterns**
// Good: Explains what the regex matches
// Match email format: username@domain.extension
const emailPattern = /^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$/;**API Constraints or Gotchas**
// Good: Explains external constraint
// GitHub API rate limit: 5000 requests/hour for authenticated users
await rateLimiter.wait();
const response = await fetch(githubApiUrl);Decision Framework
Before writing a comment, ask:
1. **Is the code self-explanatory?** → No comment needed
2. **Would a better variable/function name eliminate the need?** → Refactor instead
3. **Does this explain WHY, not WHAT?** → Good comment
4. **Will this help future maintainers?** → Good comment
Special Cases for Comments
Public APIs
/**
* Calculate compound interest using the standard formula.
*
* @param {number} principal - Initial amount invested
* @param {number} rate - Annual interest rate (as decimal, e.g., 0.05 for 5%)
* @param {number} time - Time period in years
* @param {number} compoundFrequency - How many times per year interest compounds (default: 1)
* @returns {number} Final amount after compound interest
*/
function calculateCompoundInterest(principal, rate, time, compoundFrequency = 1) {
// ... implementation
}Configuration and Constants
// Good: Explains the source or reasoning
const MAX_RETRIES = 3; // Based on network reliability studies
const API_TIMEOUT = 5000; // AWS Lambda timeout is 15s, leaving bufferAnnotations
// TODO: Replace with proper user authentication after security review
// FIXME: Memory leak in production - investigate connection pooling
// HACK: Workaround for bug in library v2.1.0 - remove after upgrade
// NOTE: This implementation assumes UTC timezone for all calculations
// WARNING: This function modifies the original array instead of creating a copy
// PERF: Consider caching this result if called frequently in hot path
// SECURITY: Validate input to prevent SQL injection before using in query
// BUG: Edge case failure when array is empty - needs investigation
// REFACTOR: Extract this logic into separate utility function for reusability
// DEPRECATED: Use newApiFunction() instead - this will be removed in v3.0Anti-Patterns to Avoid
Dead Code Comments
// Bad: Don't comment out code
// const oldFunction = () => { ... };
const newFunction = () => { ... };Changelog Comments
// Bad: Don't maintain history in comments
// Modified by John on 2023-01-15
// Fixed bug reported by Sarah on 2023-02-03
function processData() {🎯 Best For
- UI designers
- Product designers
- Claude users
- GitHub Copilot users
- Software engineers
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Self-Explanatory-Code-Commenting to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
Is Self-Explanatory-Code-Commenting compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Self-Explanatory-Code-Commenting?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Self-Explanatory-Code-Commenting?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/self-explanatory-code-commenting/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.