Architecture Performance Optimization

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Use to analyze and resolve performance bottlenecks across database, API, network, and frontend layers. It guides identifying bottleneck types, measuring baseline metrics, and applying layer-specific optimizations like indexing, caching, lazy loading, and OnPush change detection. Helpful when dealing with slow API responses, database query optimization, frontend rendering issues, or scalability planning.

Sby Skills Guide Bot
DevelopmentIntermediate
6/2/2026
Claude Code
#performance-optimization#database#api#frontend#caching

Recommended for

Automated summary

Provides a systematic approach to identify and resolve performance bottlenecks across database, API, and frontend layers.

Strengths

  • Clear step-by-step workflow for bottleneck classification
  • Covers database index optimization, API caching, and frontend lazy loading
  • Includes baseline measurement and verification steps

Limitations

  • Assumes familiarity with specific tools (curl, webpack-bundle-analyzer)
  • May not cover deep language/framework-specific optimizations
  • No guidelines for distributed system or microservices performance
When to use it

When application response times are slow or you need to systematically improve performance across the stack.

When not to use it

When the performance issue is already isolated to a single component requiring deep expertise (e.g., complex SQL query rewriting beyond indexing).

Security analysis

Safe
Quality score90/100

The skill provides guidance on performance optimization techniques across layers, with no destructive, exfiltrating, or obfuscated actions. It uses Bash for measurement tools (curl, npm) and database scripts, which are standard and safe when used as directed for analysis purposes.

No concerns found

How this analysis is made

Examples

Optimize slow API endpoint
My /api/users endpoint is taking over 2 seconds. I suspect it's a database query. Help me profile and optimize it.
Frontend bundle size reduction
The admin dashboard loads slowly due to large bundle size. How can I reduce it with code splitting and lazy loading?
Database N+1 query fix
I'm seeing many repeated database queries when fetching orders with their items. How do I detect and fix N+1?

name: arch-performance-optimization version: 1.1.0 description: '[Architecture] Use when analyzing and improving performance for database queries, API endpoints, or frontend rendering.' allowed-tools: Read, Write, Edit, Grep, Glob, Bash, Task

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI may ask user whether to skip.

Prerequisites: MUST READ .claude/skills/shared/evidence-based-reasoning-protocol.md before executing.

Quick Summary

Goal: Analyze and resolve performance bottlenecks across database, API, network, and frontend layers.

Workflow:

  1. Identify Bottleneck — Classify as database, API, network, or frontend issue
  2. Measure Baseline — Gather metrics before changes (response time, query time, bundle size)
  3. Optimize — Apply layer-specific fixes (indexes, caching, lazy loading, OnPush)
  4. Verify — Measure again and confirm improvement without regressions

Key Rules:

  • Never use SELECT * or unbounded result sets in production
  • Always use async I/O; never block threads with .Result
  • Avoid N+1 queries — use eager loading or batch fetching
  • Use bounded parallelism (ParallelAsync with maxConcurrent) for background jobs

Performance Optimization Workflow

When to Use This Skill

  • Slow API response times
  • Database query optimization
  • Frontend rendering issues
  • Memory usage concerns
  • Scalability planning

Pre-Flight Checklist

  • [ ] Identify performance bottleneck
  • [ ] Gather baseline metrics
  • [ ] Determine acceptable thresholds
  • [ ] Plan measurement approach

Performance Analysis Framework

Step 1: Identify Bottleneck Type

Performance Issue
├── Database (slow queries, N+1)
├── API (serialization, processing)
├── Network (payload size, latency)
└── Frontend (rendering, bundle size)

Step 2: Measure Baseline

# API response time
curl -w "@curl-format.txt" -o /dev/null -s "http://api/endpoint"

# Database query time (SQL Server)
SET STATISTICS TIME ON;
SELECT * FROM Table WHERE ...;

# Frontend bundle analysis
npm run build -- --stats-json
npx webpack-bundle-analyzer stats.json

Database Optimization

⚠️ MUST READ: CLAUDE.md for N+1 detection, eager loading, projection, paging, and parallel query patterns. See database-optimization skill for advanced index and query optimization.

Index Recommendations

-- Frequently filtered columns
CREATE INDEX IX_Employee_CompanyId ON Employees(CompanyId);
CREATE INDEX IX_Employee_Status ON Employees(Status);

-- Composite index for common queries
CREATE INDEX IX_Employee_Company_Status
ON Employees(CompanyId, Status)
INCLUDE (FullName, Email);

-- Full-text search index
CREATE FULLTEXT INDEX ON Employees(FullName, Email);

API Optimization

⚠️ MUST READ: CLAUDE.md for parallel tuple queries and response DTO patterns.

Caching

// Static data caching
private static readonly ConcurrentDictionary<string, LookupData> _cache = new();

public async Task<LookupData> GetLookupAsync(string key)
{
    if (_cache.TryGetValue(key, out var cached))
        return cached;

    var data = await LoadFromDbAsync(key);
    _cache.TryAdd(key, data);
    return data;
}

Frontend Optimization

Bundle Size

// :x: Import entire library
import _ from 'lodash';

// :white_check_mark: Import specific functions
import { debounce } from 'lodash-es/debounce';

Lazy Loading

// :white_check_mark: Lazy load routes
const routes: Routes = [
    {
        path: 'feature',
        loadChildren: () => import('./feature/feature.module').then(m => m.FeatureModule)
    }
];

Change Detection

// :white_check_mark: OnPush for performance
@Component({
  changeDetection: ChangeDetectionStrategy.OnPush
})

// :white_check_mark: Track-by for lists
trackByItem = this.ngForTrackByItemProp<Item>('id');

// Template
@for (item of items; track trackByItem)

Virtual Scrolling

// For large lists
import { CdkVirtualScrollViewport } from '@angular/cdk/scrolling';

<cdk-virtual-scroll-viewport itemSize="50">
  @for (item of items; track item.id) {
    <div class="item">{{ item.name }}</div>
  }
</cdk-virtual-scroll-viewport>

Background Job Optimization

⚠️ MUST READ: CLAUDE.md for bounded parallelism (ParallelAsync with maxConcurrent) and batch processing (UpdateManyAsync) patterns.

Performance Monitoring

Logging Slow Operations

var sw = Stopwatch.StartNew();
var result = await ExecuteOperation();
sw.Stop();

if (sw.ElapsedMilliseconds > 1000)
    Logger.LogWarning("Slow operation: {Ms}ms", sw.ElapsedMilliseconds);

Database Query Logging

// In DbContext configuration
optionsBuilder.LogTo(
    Console.WriteLine,
    new[] { DbLoggerCategory.Database.Command.Name },
    LogLevel.Information);

Performance Checklist

Database

  • [ ] Indexes on filtered columns
  • [ ] Eager loading for relations
  • [ ] Projection for partial data
  • [ ] Paging at database level
  • [ ] No N+1 queries

API

  • [ ] Parallel operations where possible
  • [ ] Response DTOs (not entities)
  • [ ] Caching for static data
  • [ ] Pagination for lists

Frontend

  • [ ] Lazy loading for routes
  • [ ] OnPush change detection
  • [ ] Track-by for lists
  • [ ] Virtual scrolling for large lists
  • [ ] Tree-shaking imports

Background Jobs

  • [ ] Bounded parallelism
  • [ ] Batch operations
  • [ ] Paged processing
  • [ ] Appropriate scheduling

Anti-Patterns to AVOID

:x: SELECT * in production

var all = await context.Table.ToListAsync();

:x: Synchronous I/O

var result = asyncOperation.Result;  // Blocks thread

:x: Unbounded result sets

await repo.GetAllAsync();  // Could be millions

:x: Repeated database calls in loops

foreach (var id in ids)
    await repo.GetByIdAsync(id);  // N queries

Verification Checklist

  • [ ] Baseline metrics recorded
  • [ ] Bottleneck identified and addressed
  • [ ] Changes measured against baseline
  • [ ] No new performance issues introduced
  • [ ] Monitoring in place

Related

  • arch-security-review
  • database-optimization

IMPORTANT Task Planning Notes (MUST FOLLOW)

  • Always plan and break work into many small todo tasks
  • Always add a final review todo task to verify work quality and identify fixes/enhancements

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/architecture-performance-optimization-mm78nmmh' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/architecture-performance-optimization-mm78nmmh/download' --output '.skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md.part' && mv '.skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md.part' '.skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Write, Edit, Grep, Glob, Bash, Task

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md' && test -s '.skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/arch-performance-optimization' && cp -R '.skill-downloads/architecture-performance-optimization-mm78nmmh' '.claude/skills/arch-performance-optimization'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/architecture-performance-optimization-mm78nmmh'

openskills read 'architecture-performance-optimization-mm78nmmh'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/architecture-performance-optimization-mm78nmmh/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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