code-audit
Code Audit
Comprehensive codebase quality audit using parallel explore agents. Always checks everything. Agent count and scope are user-controlled.
Arguments
Parse the user's input for:
- Agent count (required) -- how many parallel explore agents to launch. The user provides this number.
- Scope (optional) -- one of:
full(default) -- entire codebasechanged-- only files changed since last commit (git diff --name-only HEAD)staged-- only staged files (git diff --cached --name-only)branch-- files changed on current branch vs main (git diff --name-only main...HEAD)<path>-- specific directory or glob pattern (e.g.src/engine/)
If the user provides just a number, use full scope. If they provide a path, use that as scope.
Examples:
/code-audit 10-- 10 agents, full codebase
More from b4r7x/agent-skills
react-design-patterns
Use when choosing a React component pattern — custom hooks, control props, compound components, headless components, render props, container/presentational, or other architectural patterns. Includes 13 patterns with decision guide and 2025 popularity ranking.
27human-commit
Generates human-like git commit messages based on staged or unstaged changes. Reads git diff, analyzes what changed, and outputs 3 natural commit message options that sound like they were written by a developer — not AI. This skill should be used when the user wants a commit message, asks "what should I write for commit", "generate commit message", "human like commit", "wiadomość do commita", or just asks for help committing.
25humanize-readme
Rewrites a README.md to remove AI slop — buzzwords, generic openers, fake enthusiasm, and formulaic structure — replacing it with direct, honest, human-sounding writing. This skill should be used when the user wants to humanize a README, remove AI-generated writing patterns, make documentation sound less like ChatGPT wrote it, or asks to "fix the README", "humanize readme", "remove AI slop", "make it sound human".
25improve-prompt
Transforms a rough, unpolished prompt idea into a precise, structured AI coding prompt. Automatically researches the current project context (stack, file structure, conventions, git history) before generating. This skill should be used when the user provides a vague or "dirty" prompt idea and asks to refine, improve, or rewrite it — e.g. "improve this prompt", "refine my prompt", "ulepszony prompt", "dopracuj prompt", or simply describes what they want done in rough terms.
24react-anti-patterns
Use when reviewing React code — especially AI-generated code — to catch common anti-patterns. Covers 18 anti-patterns with detection difficulty, including stale closures, state mutation, useEffect abuse, and boolean explosion.
22deep-plan
Takes a rough, unpolished prompt idea and autonomously turns it into an implementation plan. Researches the project deeply, asks clarifying questions, generates a precise internal prompt, then executes it to produce a structured plan with todos. Designed for plan mode. Use when the user gives a vague feature request, rough idea, or "dirty" prompt and wants a ready-to-execute implementation plan — e.g. "plan this", "deep plan", "turn this into a plan", "zaplanuj to", "zrób plan".
20