/code:complexity

Measure and report code complexity metrics.

When to Use This Skill

Context

• Source files: !find . -type f \( -name "*.ts" -o -name "*.tsx" -o -name "*.js" -o -name "*.jsx" -o -name "*.py" -o -name "*.rs" -o -name "*.go" \) -not -path "*/node_modules/*" -not -path "*/.git/*" -not -path "*/dist/*" -not -path "*/build/*"
• Package files: !find . -maxdepth 1 \( -name "package.json" -o -name "pyproject.toml" -o -name "Cargo.toml" -o -name "go.mod" \) -type f

Parameters

• $1: Path to analyze (defaults to current directory)
• --threshold: Complexity threshold for flagging (default: 10)
• --format: Output format — summary (default), detailed, json

Metric Computation: Offload, Never Count By Hand

Complexity metrics (cyclomatic complexity, NLOC, parameter count, function length, nesting depth) are computed by a tool, never by eyeballing function boundaries or counting branches by hand. Hand-counting is token-hungry, irreproducible run-to-run, and exactly the mechanical work that belongs in a deterministic substrate.

• Language-native fast paths (use when the project already has them configured): radon for Python, cargo clippy for Rust, the ESLint complexity rule for JS/TS when an ESLint config exists.
• lizard — the uniform fallback for every language. One tool computes cyclomatic complexity (CCN), NLOC, parameter count (PARAM), function length, and nesting depth (ND) across JS/TS/Go/Python/Rust/C/C++/Java with machine-readable output. It is the deterministic answer wherever a language-native tool is absent — always the JS/TS and Go path when ESLint complexity isn't configured.

Install lizard (tool-installation priority)

uv tool install lizard

Alternative: mise use -g pipx:lizard (mise pipx: backend, runs via uvx).

Execution

Execute this complexity analysis:

Step 1: Detect project language and available tools

Check for language-specific complexity tools, falling back to lizard:

• JavaScript/TypeScript: use the ESLint complexity rule when an ESLint config is present; otherwise use lizard.
• Python: use radon (cyclomatic + maintainability index); lizard is a fallback if radon is unavailable.
• Rust: use cargo clippy cognitive-complexity warnings; lizard is a fallback.
• Go: use lizard.
• Any other language / no native tool: use lizard.

Confirm lizard is installed (uv tool install lizard) before using the fallback path.

Step 2: Measure function-level complexity

JavaScript/TypeScript (ESLint complexity rule, when configured):

npx eslint --rule '{"complexity":["warn",1]}' --format json .

JavaScript/TypeScript, Go, or any language without a native tool (lizard):

# Warnings only — one line per function exceeding the CCN threshold
lizard -C 10 --warnings_only .

# Full machine-readable metrics for every function (CSV)
lizard --csv .

lizard emits, per function: NLOC, CCN (cyclomatic complexity), token count, PARAM (parameter count), length, and ND (nesting depth) — the complete metric set, so no branch counting or line counting is done by hand. Restrict to a language when needed with -l js, -l typescript, -l go, etc. The --warnings_only run exits non-zero when any function exceeds the threshold.

CSV column order (for lizard --csv): NLOC, CCN, token, PARAM, length, location, file, function, long_name, start_line, end_line.

Python (Radon):

radon cc ${1:-.} -s -a --min B
radon mi ${1:-.} -s

Rust:

cargo clippy -- -W clippy::cognitive_complexity

Step 3: Identify hotspots

Rank files and functions by complexity. Flag items exceeding the threshold:

Step 4: Calculate file-level metrics

For each source file:

• Total functions/methods
• Average complexity per function
• Maximum complexity function
• Lines of code vs lines of logic
• Import/dependency count (coupling indicator)

The lizard default (non-CSV) run already prints per-file NLOC, average NLOC, average CCN, average token count, and function count — use it for the file-level roll-up.

Step 5: Report results

Complexity Report
=================
Files analyzed: N
Functions analyzed: N
Average complexity: X.X

Hotspots (complexity > threshold):
  File                          | Function        | CC  | Lines | Depth
  src/auth/handler.ts           | validateToken   | 15  | 82    | 6
  src/api/router.ts             | handleRequest   | 12  | 64    | 5

Distribution:
  Low (1-5):    NN% of functions
  Medium (6-10): NN% of functions
  High (11+):   NN% of functions

Recommendations:
1. [file:function] Extract nested conditions into helper functions
2. [file:function] Split into smaller focused functions
3. [file:function] Replace switch with strategy pattern

Post-Actions

• If many high-complexity functions → suggest /code:refactor for the worst offenders
• If complexity tools not installed → suggest uv tool install lizard (uniform, all languages) or pip install radon (Python)
• If setting up complexity budgets → suggest adding ESLint complexity rule via /configure:linting

Agentic Optimizations