Cyclomatic Complexity

SkillDev tools

Refactor code to reduce cyclomatic complexity so it stays readable, maintainable, and aligned with the long-term vision of the codebase, not just optimized for AI comprehension. Use whenever the user asks to refactor, simplify, clean up, or review code quality; mentions complexity, maintainability, readability, spaghetti code, deeply nested logic, or god functions; or asks to check AI-generated code before merging. Also use proactively after writing any nontrivial function with heavy branching.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Cyclomatic Complexity skill

What this skill tells your AI

The instructions your AI receives, as published by saurabhkumar8112/cyclomatic-complexity-skill in skills/cyclomatic-complexity/SKILL.md and read by ahel’s review.

Purpose: AI-written code often works but branches like a jungle. This skill: measure complexity, refactor hotspots, keep code human-maintainable.

Measure first

CC = decision points + 1. Decision points: if, else if, case, loops, catch, ternary, &&, || in conditions.

Project linter config wins. If eslintrc, radon config, sonar config, or similar sets a complexity threshold, use that. No config: use defaults below.

Thresholds:

  • 1-5: fine, leave alone
  • 6-10: watch, refactor if touching anyway
  • 11-15: refactor now
  • 15+: must split, no debate

Prefer real tools over eyeballing when environment allows:

  • Python: radon cc -s -a <path>
  • JS/TS: eslint complexity rule
  • Go: gocyclo
  • Polyglot: lizard <path>

No tool available: count manually, per function, show the count.

Refactor tactics, in order of preference

  1. Guard clauses. Invert conditions, return early, kill nesting.
  2. Extract function. Each extracted piece gets a name that says what, not how. Names are documentation.
  3. Lookup table / map instead of if-else or switch chains.
  4. Named predicates. if (isEligibleForRefund(order)) beats a 4-clause boolean soup.
  5. Polymorphism / strategy for switch-on-type. Only when the switch appears in 2+ places.
  6. Flatten loops. Extract loop body, use continue instead of nested if.

Hard rules

  • Preserve behavior. Run tests before and after. No tests: say so, suggest adding, refactor conservatively.
  • Don't game the metric. A dense one-liner hiding 6 branches is worse than the honest if-chain it replaced. Complexity should move into well-named units, not disappear into cleverness.
  • Don't break public APIs or exported signatures without asking.
  • Small functions with clear names > few functions with comments explaining sections.
  • One responsibility per function. If the name needs "and", split.

Workflow

  1. Measure all touched functions, rank by CC descending.
  2. Report hotspots with numbers before touching anything.
  3. Refactor worst first, one function at a time.
  4. Re-measure. Show before/after table: function, CC before, CC after.
  5. Verify: tests pass, behavior unchanged, diff reviewable.

Output format

End every refactor with:

## Complexity report
| Function | Before | After |
|----------|--------|-------|
| parseOrder | 14 | 4 |

Extracted: validateHeader, resolveDiscount
Behavior verified: <how>

Keep prose minimal. Numbers and diffs do the talking.

Signals

GitHub stars
384
Forks
9
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
cyclomatic-complexity
Source
github.com/saurabhkumar8112/cyclomatic-complexity-skill