name	complexity-analysis
version	1.0.0
description	Challenges over-engineering and identifies unnecessary complexity before implementation. Use when planning features, designing architecture, choosing frameworks, evaluating patterns, or when complexity, overengineering, simpler alternatives, `--complexity-analysis`, or `--keep-it-simple` are mentioned. Helps teams avoid technical debt by validating that complexity is justified.

Challenge Complexity

Systematic pushback against over-engineering → justified simplicity.

Planning features or architecture
Choosing frameworks, libraries, patterns
Evaluating proposed solutions
Detecting premature optimization or abstraction
Build vs buy decisions

NOT for: trivial tasks, clear requirements with validated complexity, regulatory/compliance-mandated approaches

Track with TodoWrite when applying framework to non-trivial proposals:

Phase	Trigger	activeForm
Identify	Complexity smell detected	"Identifying complexity smell"
Alternative	Generating simpler options	"Proposing simpler alternatives"
Question	Probing constraints	"Questioning constraints"
Document	Recording decision	"Documenting decision"

TodoWrite format:

- Identify { complexity type } smell
- Propose alternatives to { specific approach }
- Question { constraint/requirement }
- Document { decision/rationale }

Workflow:

Start: Create Identify in_progress when smell detected
Transition: Mark current completed, add next in_progress
Skip to Document if complexity validated immediately
Optional phases: skip Alternative if obvious, skip Question if constraints clear

Adjust tone based on severity:

◇ Alternative (Minor complexity):

"Interesting approach. Help me understand why X over the more common Y?"

◆ Caution (Moderate risk):

"This pattern often leads to [specific problems]. Are we solving for something I'm not seeing?"

◆◆ Hazard (High risk):

"This violates [principle] and will likely cause [specific issues]. I strongly recommend [alternative]. If we must proceed, we need to document the reasoning."

Common complexity smells to watch for:

Build vs Buy: Custom solution when proven libraries exist

Custom auth system → Auth0, Clerk, BetterAuth
Custom validation → Zod, Valibot, ArkType
Custom state management → Zustand, Jotai, Nanostores
Custom form handling → React Hook Form, Formik

Indirect Solutions: Solving problem A by first solving problems B, C, D

Compiling TS→JS then using JS → Use TS directly in build tool
Reading file, transforming, writing back → Use stream processing
Storing in DB to pass between functions → Pass data directly

Premature Abstraction: Layers "for flexibility" without concrete future requirements

Plugin systems for 1 use case
Factories for single implementations
Dependency injection for stateless functions
Generic repositories for 1 data source

Performance Theater: Optimizing without measurements or clear bottlenecks

Caching before measuring load
Debouncing without user complaints
Worker threads for CPU-light tasks
Memoization of cheap calculations

Security Shortcuts: Disabling security features instead of configuring properly

CORS: * → Configure specific origins
any types for external data → Runtime validation with Zod
Disabling SSL verification → Fix certificate chain
Storing secrets in code → Environment variables + vault

Framework Overkill: Heavy frameworks for simple tasks

React for static content → HTML + CSS
Redux for local UI state → useState
GraphQL for simple CRUD → REST
Microservices for small apps → Monolith first

Custom Infrastructure: Building platform features that cloud providers offer

Custom logging → CloudWatch, Datadog
Custom metrics → Prometheus, Grafana
Custom secrets → AWS Secrets Manager, Vault
Custom CI/CD → GitHub Actions, CircleCI

Watch for these justifications — reframe with specific questions:

"We might need it later" → "What specific requirement do we have now?"

"It's more flexible" → "What flexibility do we need that the simple approach doesn't provide?"

"It's best practice" → "Best practice for what context? Does that context match ours?"

"It's faster" → "Have you measured? What's the performance requirement?"

"Everyone does it this way" → "For problems of this scale? Do they have our constraints?"

"It's more enterprise-ready" → "What enterprise requirement are we meeting?"

"I read about it on Hacker News" → "Does their problem match ours?"

Guide toward simpler alternatives with concrete examples:

Feature Flags over Plugin Architecture

// Complex
interface Plugin { transform(data: Data): Data }
const plugins = loadPlugins()
let result = data
for (const plugin of plugins) { result = plugin.transform(result) }

// Simple
const features = getFeatureFlags()
let result = data
if (features.transformA) { result = transformA(result) }
if (features.transformB) { result = transformB(result) }

Direct over Generic

// Complex (premature abstraction)
interface DataStore<T> { get(id: string): Promise<T> }
class PostgresStore<T> implements DataStore<T> { /* ... */ }
const users = new PostgresStore<User>({ /* config */ })

// Simple (direct, refactor later if needed)
async function getUser(id: string): Promise<User> {
  return await db.query('SELECT * FROM users WHERE id = $1', [id])
}

Standard Library over Framework

// Complex
import _ from 'lodash'
const unique = _.uniq(array)
const mapped = _.map(array, fn)

// Simple
const unique = [...new Set(array)]
const mapped = array.map(fn)

Composition over Configuration

// Complex
const pipeline = new Pipeline({
  steps: [
    { type: 'validate', rules: [...] },
    { type: 'transform', fn: 'normalize' },
    { type: 'save', destination: 'db' }
  ]
})

// Simple
const result = pipe(
  data,
  validate,
  normalize,
  save
)

Complexity is appropriate when:

Measured Performance Need: Profiling shows bottleneck, optimization addresses it
Proven Scale Requirement: Current scale breaking, specific metric to meet
Regulatory Compliance: Legal requirement for specific implementation
Security Threat Model: Documented threat that simpler approach doesn't address
Integration Contract: External system requires specific approach
Team Expertise: Team has deep expertise in complex pattern but not simple one

Even then:

Document why in ADR
Add TODO to revisit when constraints change
Isolate complexity to smallest possible scope
Provide escape hatches

Apply this protocol systematically:

1. IDENTIFY → Recognize complexity smell

Scan proposal for common triggers:

Build vs Buy
Indirect Solutions
Premature Abstraction
Performance Theater
Security Shortcuts
Framework Overkill
Custom Infrastructure

2. ALTERNATIVE → Propose simpler solutions

Always provide concrete, specific alternatives with examples:

❌ Vague: "Maybe use something simpler?" ✅ Specific: "Use Zod for validation instead of building a custom validation engine. Here's how..."

Include:

Exact library/pattern name
Code snippet showing simpler approach
Why it's sufficient for actual requirements

3. QUESTION → Investigate constraints

Ask probing questions to uncover hidden requirements:

"What specific requirement makes the simpler approach insufficient?"
"What will break in 6 months if we use the standard pattern?"
"What performance/scale problem are we solving?"
"What security threat model requires this complexity?"
"What team capability gap makes the standard approach unsuitable?"

4. DOCUMENT → Record decisions

If complexity chosen after validation:

Document specific requirement that justifies it
Add ADR (Architecture Decision Record) explaining trade-offs
Include TODO for revisiting when requirements change
Add comments explaining non-obvious complexity

ALWAYS:

Apply pushback protocol to non-trivial proposals
Provide concrete alternatives with code examples
Ask specific questions about constraints
Match escalation level to severity (◇/◆/◆◆)
Document justified complexity decisions

NEVER:

Accept "might need it later" without concrete timeline
Allow security shortcuts without threat model
Skip questioning performance claims without measurements
Proceed with indirection without clear justification
Accept complexity without documenting why

decision-framework.md — full decision checklist
redux-overkill.md — challenging Redux for simple form
custom-auth.md — challenging custom auth build

complexity-analysis

Install Skill

SKILL.md

Challenge Complexity

1. IDENTIFY → Recognize complexity smell

2. ALTERNATIVE → Propose simpler solutions

3. QUESTION → Investigate constraints

4. DOCUMENT → Record decisions