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Code Commenting Checklists

Community
kitchen-engineer42
code-commenting-checklists

Use specific checklists to ensure comprehensive and high-quality code commenting for general code, data declarations, and program structures. Apply when writing new code, reviewing existing code, or conducting code reviews to ensure completeness and quality of documentation.

Overview

Publisherkitchen-engineer42
Repositorypdf2skills
Skill namecode-commenting-checklists
Stars
136
Forks
34
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kitchen-engineer42 on GitHub. Read the source before you install it.

Installation

Install the Code Commenting Checklists AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kitchen-engineer42/pdf2skills/tree/main/skills_samples/Steve%20McConnell%20Code%20Complete%20A%20Practical%20Handbook%20of%20Software%20Construction_output/code-commenting-checklists
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable Code Commenting Checklists in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Commenting Checklists on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Commenting Checklists is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Commenting Checklists

When to Use This Skill

  • Writing or reviewing code comments
  • Conducting code reviews
  • Establishing code quality standards
  • Onboarding new developers to commenting practices
  • Preparing code for maintenance or handoff

General Comment Techniques Checklist

Apply this checklist to ensure overall comment quality:

  • Understandability: Can others immediately pick up the code and understand it?
  • Intent explanation: Does the comment explain the intent or summarize functionality, rather than repeating the code?
  • PPP usage: Was Pseudocode Programming Process used to reduce commenting time?
  • Refactoring first: Was tricky code rewritten instead of just adding comments?
  • Currency: Are comments up-to-date with the current code?
  • Clarity: Are comments clear and correct?
  • Maintainability: Does the comment style allow easy modification?

Data Declaration Comment Rules

Apply this checklist when declaring variables, constants, and data structures:

  • Units: Are units of measurement commented? (e.g., // milliseconds, // kilograms)
  • Value ranges: Are valid ranges for numeric data commented?
  • Encoding meanings: Are coded values explained? (e.g., status codes, enum values)
  • Input constraints: Are restrictions on input data documented?
  • Flag documentation: Are flags documented to the bit level?
  • Global variables (declaration): Is each global variable commented at its declaration?
  • Global variables (usage): Is each global variable identified at every use via naming convention, comment, or both?
  • Magic numbers: Are magic numbers replaced with named constants rather than just documented?

Program Structure and File Comment Rules

Apply this checklist for subprograms, functions, classes, and files:

  • Subprogram purpose: Is the purpose of each subprogram commented?
  • Subprogram details: Are additional facts included when appropriate?
    • Input and output data
    • Interface assumptions
    • Limitations and constraints
    • Error correction behavior
    • Global effects
    • Algorithm sources
  • Control structures: Is each control statement commented?
  • Complex structure endings: Are long/complex control structure endings commented, or simplified to eliminate the need?
  • Program overview: Is there a short document providing an overall view of program organization?
  • File purpose: Is the purpose of each file described?
  • Author information: Does the file include author name, email, and phone number?

Usage Guidelines

During Code Writing

  1. Write comments as you write code
  2. Apply relevant checklist items before committing
  3. Review against all applicable checklists during self-review

During Code Review

  1. Use checklists as review criteria
  2. Flag missing items for correction
  3. Track common violations for team improvement

For Legacy Code

  1. Prioritize critical sections first
  2. Focus on data declarations and public interfaces
  3. Document complex logic before simple code

Common Violations to Watch

Data Declarations

javascript
// BAD: No units or range
let timeout = 5000;

// GOOD: Complete documentation
// Timeout in milliseconds for API calls (range: 1000-30000)
let timeout = 5000;

Magic Numbers

python
# BAD: Magic number documented but not replaced
# Days in a year (365)
days = 365

# GOOD: Named constant
DAYS_IN_YEAR = 365
days = DAYS_IN_YEAR

Global Variables

java
// BAD: Global used without identification
public static int count;
// ... later ...
count++;

// GOOD: Clearly identified at usage
public static int g_userCount;  // Global: total active users
// ... later ...
g_userCount++;  // Global: increment active user count

Control Structures

javascript
// BAD: Complex structure without comment
for (let i = 0; i < items.length; i++) {
  for (let j = i + 1; j < items.length; j++) {
    if (items[i] > items[j]) {
      // swap
    }
  }
}

// GOOD: Commented or simplified
// Bubble sort: compare each pair and swap if out of order
for (let i = 0; i < items.length; i++) {
  for (let j = i + 1; j < items.length; j++) {
    if (items[i] > items[j]) {
      swap(items, i, j);
    }
  }
}

Frequently asked questions

What does the Code Commenting Checklists AI skill do?

Use specific checklists to ensure comprehensive and high-quality code commenting for general code, data declarations, and program structures. Apply when writing new code, reviewing existing code, or conducting code reviews to ensure completeness and quality of documentation.

Why use Code Commenting Checklists on TypingMind?

Because you install it once and use it with any model. Code Commenting Checklists is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Commenting Checklists in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kitchen-engineer42/pdf2skills/tree/main/skills_samples/Steve%20McConnell%20Code%20Complete%20A%20Practical%20Handbook%20of%20Software%20Construction_output/code-commenting-checklists. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Code Commenting Checklists?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Commenting Checklists?

As many as you like. As long as a model supports skills, you can use Code Commenting Checklists with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Commenting Checklists AI skill free?

It is published on GitHub by kitchen-engineer42. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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