agentleFS
JeremyMorganJeremyMorgan/code-review-skills/skills/readability-and-naming/SKILL.md

readability-and-naming

Skill15 starsChanged 5 months agoCC0-1.0View on GitHub

Reviews readability, naming conventions, and clarity, flagging confusing identifiers and structure. Use when auditing for readability, naming consistency, or style.

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    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:

    If no target path is given above, review the entire codebase.

    line 14
  2. Distinctive:

    Prefer minimal, drop-in fix snippets over prose.

    line 62
  3. Distinctive:

    Do not invent files or functions that aren’t present.

    line 64
  4. Distinctive:

    Write this into a markdown file and place it in the audits/ folder.

    line 66

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 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

Target: $ARGUMENTS

If no target path is given above, review the entire codebase.


Evaluate our code for readability and naming.

Review:

  1. NAMING CONVENTIONS
    • Variables: descriptive vs cryptic (e.g., 'u' vs 'user')
    • Functions: verb-based, clear intent
    • Classes: noun-based, single responsibility
    • Constants: UPPER_CASE consistency
    • Private methods: underscore convention
  2. NAMING CONSISTENCY
    • camelCase vs snake_case mixing
    • Abbreviation consistency
    • Domain terminology usage
    • British vs American spelling
  3. CODE READABILITY
    • Self-documenting code
    • Need for comments (too many = code smell)
    • Magic numbers/strings
    • Complex boolean expressions
    • Ternary operator abuse
  4. FUNCTION SIGNATURES
    • Parameter count (>3 is a smell)
    • Boolean parameters (avoid)
    • Optional parameter handling
    • Return type clarity

In the audit report, document a naming convention guide based on findings.

Provide:

A structured finding report

A scale of 1/10 on how important each finding is

Remediation: precise code-level fix or config change (snippets welcome) if possible

Constraints & style:

Be concrete and cite exact code locations and identifiers.

Prefer minimal, drop-in fix snippets over prose.

Do not invent files or functions that aren’t present; if context is missing, mark as Unable to verify and say what code would prove it.

Write this into a markdown file and place it in the audits/ folder.

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.