| name | refactor-agent |
| description | Use when restructure code to improve readability, maintainability, extensibility without changing external behavior. |
| domain | agents |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | ai-agents |
| tags | ["agent","ai-agent","automation","refactor","coding"] |
| version | 1.0.0 |
Refactor Agent
Quick Reference — see parent for full agent ecosystem.
The Refactor Agent restructures code to improve readability, maintainability, and extensibility without changing external behavior. It systematically identifies high-complexity functions, duplicated logic, dead code, and tightly coupled modules; then applies targeted refactorings (extract method, split module, introduce interface, remove duplication) with verification that all existing tests still pass. Its mantra: make the change easy, then make the easy change.
When Not to Use
- Simple or one-off tasks — if the task is straightforward, direct execution is faster than structured methodology.
- Already established workflows — follow existing team conventions rather than introducing new frameworks.
- When automation overhead exceeds benefit — for very small scopes, the setup cost may not be justified.
Dependencies
- Python 3.8+ or Node.js 18+
- Access to relevant APIs/services for your specific use case
- Basic understanding of the domain concepts
Commands
Key Responsibilities
- Measure complexity: Calculate cyclomatic complexity, cognitive complexity, and coupling metrics to identify the files that need refactoring most
- Apply pattern-driven refactors: Extract methods, split monoliths, introduce abstractions, remove dead code — each with a defined before/after signature
- Preserve behavior: Run the full test suite before and after every refactoring step to confirm zero behavioral changes
Code Example
"""Minimal refactor agent pattern — analyze and restructure."""
import json, sys
from pathlib import Path
def analyze_complexity(file_path: str) -> dict:
"""Analyze a file for refactoring candidates."""
content = Path(file_path).read_text()
lines = content.split("\n")
functions = []
current_fn = None
fn_lines = 0
branch_count = 0
for i, line in enumerate(lines):
stripped = line.strip()
if stripped.startswith("def ") or stripped.startswith("async def "):
if current_fn:
functions.append({
"name": current_fn, "lines": fn_lines,
"branches": branch_count, "line": i - fn_lines + 1
})
current_fn = stripped.split("(")[0].replace("def ", "").replace("async ", "")
fn_lines = 1
branch_count = 0
elif current_fn:
fn_lines += 1
if any(kw in stripped for kw in ["if ", "elif ", "for ", "while ", , ]):
branch_count +=
current_fn:
functions.append({
: current_fn, : fn_lines,
: branch_count, : (lines) - fn_lines +
})
candidates = [f f functions f[] > f[] > ]
{
: file_path, : (lines),
: functions,
: candidates,
: [
c candidates
]
}
__name__ == :
result = analyze_complexity(sys.argv[])
(json.dumps(result, indent=))
Checklist
Workflow
- Identify the task or trigger.
- Prepare inputs and configure parameters.
- Execute the core routine.
- Verify the output against expected results.
- Iterate based on feedback or new data.
Anti-Rationalization Table
| Rationalization | Reality |
|---|
| "It works, do not touch it" | Working-but-complex code has the highest bug rate per line. Refactoring now prevents production incidents later |
| "I will refactor while adding the feature" | Mixing refactoring with feature work creates unreviewable diffs and hides regressions in the noise |
| "The tests are fragile, I cannot refactor" | Fragile tests are the exact reason to refactor first — make the code testable before making the easy change |
When to Use
Use before adding features to complex code, when cyclomatic complexity exceeds team thresholds, when duplicate code spans multiple files, when dead code clutters navigation, and when migrating from old patterns to modern alternatives. Do NOT use for auto-generated code, vendored dependencies, or code scheduled for complete replacement.
