complexity

name	complexity
description	Find focused refactor hotspots.
practices	["code-complete","refactoring"]
hexagonal_role	domain
consumes	["doc","standards"]
produces	["stdout"]
context_rel	[{"kind":"shared-kernel","with":"standards"}]
skill_api_version	1
context	{"window":"fork","intent":{"mode":"task"},"sections":{"exclude":["HISTORY"]},"intel_scope":"topic"}
metadata	{"tier":"execution","dependencies":["standards","doc"]}
output_contract	stdout: complexity metrics report

Complexity Skill

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Analyze code complexity to identify refactoring targets.

Execution Steps

Given /complexity [path]:

Step 1: Determine Target

If path provided: Use it directly.

If no path: Use current directory or recent changes:

git diff --name-only HEAD~5 2>/dev/null | grep -E '\.(py|go)$' | head -10

Step 2: Detect Language

# Check for Python files
ls *.py **/*.py 2>/dev/null | head -1 && echo "Python detected"

# Check for Go files
ls *.go **/*.go 2>/dev/null | head -1 && echo "Go detected"

Step 3: Run Complexity Analysis

For Python (using radon):

# Check if radon is installed
which radon || pip install radon

# Run cyclomatic complexity
radon cc <path> -a -s

# Run maintainability index
radon mi <path> -s

For Go (using gocyclo):

# Check if gocyclo is installed
which gocyclo || go install github.com/fzipp/gocyclo/cmd/gocyclo@latest

# Run complexity analysis
gocyclo -over 10 <path>

Step 4: Interpret Results

Cyclomatic Complexity Grades:

Grade	CC Score	Meaning
A	1-5	Low risk, simple
B	6-10	Moderate, manageable
C	11-20	High risk, complex
D	21-30