Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ArabelaTso/Skills-4-SE --skill code-comment-generatorgit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/arabelatso/skills-4-se/code-comment-generator)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/code-comment-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/code-comment-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/code-comment-generator"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/code-comment-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.04447 |
| Opus 5.5 | $0.00036 | $0.01779 |
| Sonnet 5.5 | $0.00018 | $0.00889 |
| Haiku 4.5 | $0.00009 | $0.00445 |
Grade A, and why
code-comment-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 664 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Comment Generator
Generate meaningful, maintainable comments and documentation for your code.
Core Capabilities
This skill helps you create effective code documentation by:
- Analyzing code context - Understanding what the code does and why
- Matching existing style - Following comment conventions in your codebase
- Writing clear documentation - Creating function/method/class documentation
- Adding inline explanations - Explaining complex logic and algorithms
- Inserting code annotations - Adding TODO, FIXME, and optimization notes
Comment Generation Workflow
Step 1: Analyze Existing Comment Style
Before generating comments, examine the codebase to match style:
Look for:
- Documentation format (docstrings, Javadoc, etc.)
- Comment verbosity level (detailed vs. concise)
- Naming conventions and terminology
- Use of examples in documentation
- Type annotation style
Python Example - Analyze Existing Style:
# If existing code uses this pattern:
def get_user(user_id: int) -> User:
"""
Retrieve user by ID.
Args:
user_id: Unique identifier for the user
Returns:
User object if found
Raises:
UserNotFoundError: If user doesn't exist
"""
return db.query(User).get(user_id)
Style Identified:
- Google-style docstrings
- Type hints in signature
- Concise summary line
- Args/Returns/Raises sections
- No examples included
Java Example - Analyze Existing Style:
// If existing code uses this pattern:
/**
* Retrieves a user by their unique identifier.
*
* @param userId the unique identifier for the user
* @return the User object if found
* @throws UserNotFoundException if no user exists with the given ID
*/
public User getUser(int userId) throws UserNotFoundException {
return database.findUser(userId);
}
Style Identified:
- Standard Javadoc format
- Brief summary sentence
- @param, @return, @throws tags
- Formal tone
- No code examples
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 664 lines · 91 tokens per session scan A d32d6cdeccc0
code-comment-generator is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (258 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 91 tokens to every session and 4,447 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
skill-code-quality
This skill should be used when implementing code quality standards, setting up linting/testing/security scans, enforcing coverage thresholds, or establishing CI/CD guardrails.
skill-pr-review
Comprehensive code review for pull requests using parallel multi-agent analysis. Audits CLAUDE.md compliance, checks for bugs, analyzes git history, reviews comments, and filters by confidence score. Use when reviewing a GitHub PR, mentions "code review", "review this PR", or "/code-review".
teach
Teach the user a new skill or concept, within this workspace.
improve-codebase-architecture
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
skill-developer-relations
SDK development, external developer communication, code samples, API client libraries, community engagement, and developer experience. Use when creating SDKs, writing external guides, creating code samples, or improving developer experience.
diagnose
Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.