naming-analyzer_skill

This skill analyzes code names and suggests clearer, consistent alternatives for variables, functions, classes, and other identifiers.
  • Python

273

GitHub Stars

2

Bundled Files

3 weeks ago

Catalog Refreshed

2 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstart where the catalogue uses aiagentskills.

npx veilstart add skill softaworks/agent-toolkit --skill naming-analyzer

  • README.md7.2 KB
  • SKILL.md9.0 KB

Overview

This skill suggests better variable, function, and class names based on context and established conventions. It inspects code, configuration, and API surfaces to find unclear, misleading, or inconsistent identifiers and proposes concrete, actionable replacements. The output prioritizes readability, language-appropriate style, and project consistency. Suggestions include reasoning and severity so you can triage refactors.

How this skill works

The analyzer parses identifiers across files, functions, classes, constants, database columns, and API endpoints. It detects issues like vague names, harmful abbreviations, boolean naming mistakes, convention violations, and misleading names that don’t match behavior. For each finding it gives a suggested name, the rationale, and a severity level (critical, major, minor). It can also recommend project-wide conventions and produce a prioritized renaming plan.

When to use it

  • Before a major refactor or public API change to avoid introducing confusing names
  • During code reviews to catch vague or misleading identifiers early
  • When onboarding or auditing a legacy codebase with mixed naming styles
  • While preparing library or public-facing modules to comply with language conventions
  • To generate a prioritized checklist for incremental renaming and migration

Best practices

  • Prefer full descriptive words over obscure abbreviations; allow well-known acronyms (api, html, id)
  • Follow language-specific conventions (snake_case for Python, camelCase for JS functions, PascalCase for classes)
  • Use is/has/can/should prefixes for booleans and verb phrases for functions
  • Avoid single-letter names outside tight loop scopes and use clear nouns for variables
  • Name constants in UPPER_SNAKE_CASE and include units when relevant (CACHE_DURATION_MS)

Example use cases

  • Scan a repository to produce a naming analysis report with counts and severity tiers
  • Suggest replacements for a set of functions that perform side effects but are named like getters
  • Standardize boolean properties across a project to use consistent prefixes
  • Convert mixed naming conventions in a legacy folder to the project standard
  • Generate a refactoring plan that lists high-priority misleading names and lower-priority style fixes

FAQ

Yes — the analyzer can produce a refactor script that renames identifiers and updates references, with options to preserve git history and generate a migration guide.

Does it enforce one fixed convention for all projects?

No — it recommends language-appropriate defaults but respects and validates project-specific patterns when provided.

Will it flag well-known abbreviations as issues?

No — common, widely understood abbreviations (api, html, url, id) are allowed; unclear or custom abbreviations are flagged.

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