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DanielPodolsky

performance-gate

by DanielPodolsky

AI-mentored development for junior engineers. Claude becomes your mentor, not your coder — guiding with questions, reviewing via 6 Gates, but YOU write every line. Less dependency, more ownership.

1🍴 0📅 Jan 25, 2026

SKILL.md


name: performance-gate description: | TRIGGERS: "performance check before merge", "will this scale?", "ready to deploy", performance verification, scalability check, N+1 detection, optimization review. USE WHEN: Code is ready to merge and needs performance verification. PROVIDES: N+1 query detection, complexity analysis, scalability assessment. GATE TYPE: WARNING - Recommends optimization before merge.

Gate 4: Performance Review

"Code that works is step one. Code that scales is step two."

Purpose

This gate catches performance anti-patterns before they cause problems. The focus is on obvious issues, not micro-optimizations.

Gate Status

  • PASS — No obvious performance issues
  • WARNING — Issues found that could cause problems at scale

Gate Questions

Question 1: Scalability

"What happens when there are 10,000 items? 1,000,000?"

Looking for:

  • Awareness of data growth
  • Pagination for large datasets
  • Efficient data structures
  • No unnecessary loops

Question 2: Query Efficiency

"How many database queries does this operation make?"

Looking for:

  • No N+1 queries
  • Bulk operations where appropriate
  • Indexes on queried columns
  • Awareness of query cost

Question 3: Re-render Awareness (Frontend)

"When this state changes, what components re-render?"

Looking for:

  • Awareness of render triggers
  • Appropriate memoization
  • State placement optimization
  • No expensive computations in render

Performance Checklist

Database Operations

  • No N+1 queries (queries inside loops)
  • Pagination for list endpoints
  • Indexes on frequently queried columns
  • SELECT only needed columns (not SELECT *)

Frontend Rendering

  • Expensive computations use useMemo
  • Event handlers use useCallback where needed
  • Large lists use virtualization
  • Heavy components are lazy loaded

API & Network

  • Response payloads are minimal
  • Large data is paginated
  • Caching headers where appropriate
  • No redundant API calls

General

  • No nested loops (O(n²)) without justification
  • No blocking operations
  • Cleanup of intervals/timeouts
  • Reasonable memory usage

Response Templates

If PASS

✅ PERFORMANCE GATE: PASSED

Performance considerations look good:
- Data fetching is efficient
- No obvious N+1 patterns
- Appropriate pagination in place

Moving to the next gate...

If WARNING

⚠️ PERFORMANCE GATE: WARNING

Found [X] performance concerns:

**Issue 1: [N+1 Query / Inefficient Loop]**
Location: `file.ts:42`
Question: "This makes [N] queries. Can we batch into 1?"

**Issue 2: [Missing Pagination]**
Location: `file.ts:88`
Question: "What happens with 100,000 records?"

**Issue 3: [Expensive Render]**
Location: `Component.tsx:15`
Question: "Does this need to recalculate on every render?"

These may not matter now, but will become problems as the app grows.

Common Issues to Check

1. The N+1 Query Problem

❌ const users = await User.findAll();
   for (const user of users) {
     user.posts = await Post.findByUserId(user.id);
   }
   // 1 + N queries!

✅ const users = await User.findAll({
     include: [{ model: Post }]
   });
   // 1 query with JOIN

2. Fetching Everything

❌ // Returns 10,000 users with 50 fields each
   GET /api/users

✅ // Paginated with only needed fields
   GET /api/users?page=1&limit=20&fields=id,name,email

3. Expensive Render Calculations

❌ function UserList({ users }) {
     // Runs on every render
     const sorted = users.sort((a, b) => a.name.localeCompare(b.name));
     return <ul>{sorted.map(...)}</ul>;
   }

✅ function UserList({ users }) {
     const sorted = useMemo(
       () => [...users].sort((a, b) => a.name.localeCompare(b.name)),
       [users]
     );
     return <ul>{sorted.map(...)}</ul>;
   }

4. Inline Functions Causing Re-renders

❌ function Parent() {
     return <Child onClick={() => doSomething()} />;
     // New function every render → Child re-renders
   }

✅ function Parent() {
     const handleClick = useCallback(() => doSomething(), []);
     return <Child onClick={handleClick} />;
   }

5. Missing Cleanup

❌ useEffect(() => {
     const interval = setInterval(fetchData, 5000);
     // Memory leak! Runs forever
   }, []);

✅ useEffect(() => {
     const interval = setInterval(fetchData, 5000);
     return () => clearInterval(interval);
   }, []);

Socratic Performance Questions

Instead of pointing out the fix, ask:

  1. "How many queries does this endpoint execute for 100 users?"
  2. "If I add 10,000 more items, what breaks?"
  3. "Does this array get re-sorted on every render?"
  4. "What clears this interval when the component unmounts?"
  5. "Do we need all 50 columns from this table?"

Big O Quick Reference

PatternComplexity10,000 itemsConcern Level
Map lookupO(1)1 opFine
Single loopO(n)10,000 opsUsually fine
Nested loopO(n²)100M opsWarning
Triple loopO(n³)1T opsCritical

Performance Red Flags

FlagQuestionWhy
Query in a loop"Can we batch?"N+1 problem
No pagination"What at scale?"Memory/time explosion
SELECT *"Need all fields?"Wasted bandwidth
setInterval no cleanup"What clears this?"Memory leak
Inline object/function in JSX"New reference?"Unnecessary re-renders
Array.sort() in render"Cached?"Runs every render

When to NOT Worry

Not everything needs optimization:

  • Small datasets: Don't paginate 20 items
  • Rare operations: One-time admin scripts can be slow
  • Prototype phase: Get it working first
  • Micro-optimizations: Focus on algorithms, not for vs forEach

The gate is about catching obvious issues, not micro-optimization.

Score

Total Score

75/100

Based on repository quality metrics

SKILL.md

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0/15
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1ヶ月以内に更新

+10
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0/5
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+5
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+5
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