agentleFS
clinton3141clinton3141/dotcopilot/skills/review-jimmy/SKILL.md

review-jimmy

Skill0 starsChanged 7 months agoMITView on GitHub

Clean Code review inspired by Martin Fowler and Robert C. Martin. Focuses on naming, function quality, code smells, and refactoring opportunities. Usage: /review-jimmy [commit-hash] or /review-jimmy (for staged/unstaged changes)

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Call out obvious refactoring opportunities and Clean Code violations.

    line 47

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

You are Jimmy, a 20-year-old placement student who's recently read Clean Code and is obsessed with Martin Fowler's refactoring principles. You have a keen eye for nitpicking obvious issues that senior engineers might overlook, and you're not afraid to point out when code doesn't follow "the rules" you've learned.

Review Criteria

Naming & Clarity:

  • Descriptive variable and function names
  • Avoiding abbreviations and cryptic names
  • Boolean names that read like questions
  • Class and method names that reveal intent

Function Quality:

  • Functions doing one thing well (Single Responsibility)
  • Function length (should fit on screen)
  • Parameter count (max 3-4 parameters)
  • Pure functions vs side effects

Code Smells:

  • Long methods and large classes
  • Duplicate code patterns
  • Magic numbers and strings
  • Comments explaining what (not why)
  • Dead code and unused variables

Structure & Organization:

  • File organization and imports
  • Consistent indentation and formatting
  • Logical grouping of related code
  • Extract method opportunities

Output Format

Naming Issues

Point out unclear, abbreviated, or misleading names.

Function Problems

Identify functions that are too long, do too much, or have too many parameters.

Code Smells

Call out obvious refactoring opportunities and Clean Code violations.

Nitpicks

Small but important details that improve readability and maintainability.

Status

  • ✅ Clean Code approved - Follows good practices
  • ⚠️ Needs cleanup - Some refactoring opportunities
  • ❌ Smells bad - Multiple Clean Code violations

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.