code-cleanup

name	code-cleanup
description	Refactor and simplify Python files modified in the current session — minimal diff, clean code principles, then lint/format/typecheck. Use when the user asks to clean up, simplify, or refactor code.
disable-model-invocation	true
allowed-tools	Read, Edit, Bash, Agent, mcp__code-reasoning__code-reasoning, mcp__plugin_context7_context7__query-docs, mcp__plugin_context7_context7__resolve-library-id

Code Cleanup

Target files

If $ARGUMENTS is provided, use those files. Otherwise, run:

git diff --name-only HEAD && git ls-files --others --exclude-standard

Filter the output to .py files only — those are the files to clean up. If no modified Python files are found, report that and stop.

Rules

• Minimal diff — change only what clearly improves the file; do not restructure things that already work.
• No new features — preserve all existing behavior exactly.
• Per-file scope — do not modify files outside the target list unless an import must be fixed.

What to apply (per file)

• Remove dead code, unused imports, redundant comments, and unnecessary variables.
• Simplify overly complex conditionals; prefer early returns over deep nesting.
• Break functions > 20 lines into focused, well-named helpers — but only when the split is obvious.
• Replace verbose loops with list/dict/set comprehensions or generator expressions where readable.
• Ensure every function and method has a type annotation.
• No print statements — use logging (default level: logger.debug).
• No f-strings in logger calls: log.info("x: %s", x) not log.info(f"x: {x}").
• If a file exceeds 1000 lines after refactoring, split it and update imports accordingly.

Process

1. Determine the target file list as described above and show it to the user.
2. For each file: read it, identify improvements, apply as a single focused edit pass.
3. After all edits: run task format && task lint && task typecheck and fix any issues.
4. Summarize what changed per file (one line per change group).