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performance-optimization性能优化

Agent Skill

performance-optimization 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

259

周安装

11

GitHub Stars

219

下载量

91
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:performance-optimization(性能优化)
来源仓库:https://github.com/hack23/cia
仓库路径:skills/performance-optimization
安装命令:
npx skills add https://github.com/hack23/cia --skill performance-optimization
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hack23/cia --skill performance-optimization

简介

performance-optimization 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于需要根据关键词或任务场景从来源线索中获取信息的场景。
  • 通过关键词、任务场景或来源线索进行信息检索与筛选。
  • 安装命令:npx skills add https://github.com/hack23/cia --skill performance-optimization。
  • 建议确认权限范围、维护状态及是否触发联网或文件读写操作。

SKILL.md

Performance Optimization Skill

Purpose

This skill provides performance optimization guidance for the CIA platform across JVM tuning, PostgreSQL query optimization, Vaadin UI rendering, and Spring Framework efficiency. It ensures the political intelligence platform delivers responsive analysis to users.

When to Use This Skill

Apply this skill when:

  • ✅ Diagnosing slow page loads or API response times
  • ✅ Optimizing database queries for large political datasets
  • ✅ Tuning JVM parameters for production deployment
  • ✅ Improving Vaadin UI component rendering performance
  • ✅ Reducing memory consumption in data processing pipelines
  • ✅ Optimizing materialized view refresh schedules
  • ✅ Profiling Spring application startup time

Do NOT use for:

  • ❌ Security hardening (use security-by-design skill)
  • ❌ Feature development without performance concerns
  • ❌ UI styling changes that don't affect rendering

Performance Targets

MetricTargetMeasurement
Page load time< 3 secondsLighthouse, browser DevTools
API response time< 500ms (p95)CloudWatch metrics
Database query time< 100ms (p95)PostgreSQL pg_stat_statements
JVM heap usage< 80% of maxJMX / CloudWatch
Vaadin push latency< 200msClient-side measurement
Startup time< 30 secondsApplication logs

JVM Optimization

Recommended JVM Settings

# Production JVM flags for CIA platform (Java 21+)
JAVA_OPTS="-server \
  -Xms2g -Xmx4g \
  -XX:+UseG1GC \
  -XX:MaxGCPauseMillis=200 \
  -XX:+UseStringDeduplication \
  -XX:+OptimizeStringConcat \
  -XX:MetaspaceSize=256m \
  -XX:MaxMetaspaceSize=512m \
  -XX:+HeapDumpOnOutOfMemoryError \
  -XX:HeapDumpPath=/var/log/cia/heapdump.hprof \
  -Djava.security.egd=file:/dev/./urandom"

Memory Optimization Patterns

// ✅ EFFICIENT: Stream processing for large datasets
@Service
public class VotingDataProcessor {

    @Transactional(readOnly = true)
    public void processVotingRecords(String sessionId) {
        try (Stream<VoteData> votes = voteRepository.streamBySession(sessionId)) {
            votes.map(this::analyzeVote)
                 .filter(Objects::nonNull)
                 .forEach(resultRepository::save);
        }
        // Stream auto-closes, no memory accumulation
    }
}

// ❌ INEFFICIENT: Loading all records into memory
public void processVotingRecords(String sessionId) {
    List<VoteData> allVotes = voteRepository.findBySession(sessionId);
    // May load millions of records into heap
}

PostgreSQL Query Optimization

Index Strategy for Political Data

-- High-impact indexes for common CIA queries
-- Politician lookup by party and status
CREATE INDEX idx_person_party_status
  ON person_data (party, status) WHERE status = 'ACTIVE';

-- Voting record time-series queries
CREATE INDEX idx_vote_date_committee
  ON vote_data (vote_date DESC, committee_id);

-- Document search optimization
CREATE INDEX idx_document_search
  ON document_content USING gin(to_tsvector('swedish', content));

-- Materialized view refresh tracking
CREATE INDEX idx_mv_refresh_status
  ON materialized_view_log (view_name, last_refresh DESC);

Query Anti-Patterns

// ❌ N+1 Query Problem
@Entity
public class Committee {
    @OneToMany(fetch = FetchType.LAZY)
    private List<CommitteeMember> members;
}
// Accessing committee.getMembers() in a loop = N+1 queries

// ✅ FIX: Use JOIN FETCH or EntityGraph
@Query("SELECT c FROM Committee c JOIN FETCH c.members WHERE c.id = :id")
Committee findWithMembers(@Param("id") Long id);

// ✅ FIX: Use @EntityGraph
@EntityGraph(attributePaths = {"members", "members.person"})
Committee findById(Long id);

Materialized View Optimization

-- Concurrent refresh to avoid locks during read
REFRESH MATERIALIZED VIEW CONCURRENTLY view_riksdagen_politician_summary;

-- Schedule refresh based on data freshness requirements
-- High priority: refresh every 15 minutes during business hours
-- Low priority: refresh daily during off-peak

Vaadin UI Performance

Lazy Loading for Large Datasets

// ✅ EFFICIENT: Lazy loading with DataProvider
Grid<PoliticianSummary> grid = new Grid<>(PoliticianSummary.class);
grid.setDataProvider(
    DataProvider.fromCallbacks(
        query -> politicianService.fetch(query.getOffset(), query.getLimit()),
        query -> politicianService.count()
    )
);

// ❌ INEFFICIENT: Loading all items upfront
grid.setItems(politicianService.findAll()); // Loads everything

Component Optimization

// ✅ Use virtual scrolling for long lists
grid.setPageSize(50);
grid.setMultiSort(true);

// ✅ Minimize push updates
@Push(transport = Transport.WEBSOCKET_XHR)
public class MainView extends AppLayout {
    // Only push critical real-time updates
}

// ✅ Defer non-critical UI updates
UI.getCurrent().access(() -> {
    notificationComponent.update(newData);
});

Bundle Size Reduction

  • Use @CssImport instead of inline styles for reuse
  • Enable production mode (vaadin.productionMode=true)
  • Minimize custom JavaScript in @ClientCallable methods
  • Use Vaadin's built-in components over custom widgets

Spring Framework Performance

Caching Strategy

@Service
public class PoliticianService {

    // Cache frequently accessed, rarely changing data
    @Cacheable(value = "politicians", key = "#personId",
               unless = "#result == null")
    public PoliticianSummary getPolitician(String personId) {
        return repository.findSummaryById(personId);
    }

    // Evict cache when data is updated
    @CacheEvict(value = "politicians", key = "#personId")
    public void updatePolitician(String personId, PoliticianUpdate update) {
        repository.update(personId, update);
    }
}

Transaction Optimization

// ✅ Read-only transactions for queries (no dirty checking)
@Transactional(readOnly = true)
public List<VotingSummary> getVotingSummaries(String sessionId) {
    return votingRepository.findSummariesBySession(sessionId);
}

// ✅ Batch operations for bulk inserts
@Transactional
public void importVotingData(List<VoteData> votes) {
    int batchSize = 50;
    for (int i = 0; i < votes.size(); i++) {
        entityManager.persist(votes.get(i));
        if (i % batchSize == 0) {
            entityManager.flush();
            entityManager.clear(); // Release memory
        }
    }
}

Performance Testing

JMH Benchmarks for Critical Paths

@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.MILLISECONDS)
@State(Scope.Benchmark)
public class PoliticianLookupBenchmark {

    @Benchmark
    public void benchmarkPoliticianSearch() {
        politicianService.searchByName("test");
    }
}

Monitoring Checklist

  • ✅ Enable pg_stat_statements for query analysis
  • ✅ Configure JMX export for JVM metrics
  • ✅ Set up CloudWatch dashboards for response times
  • ✅ Monitor Vaadin session count and memory usage
  • ✅ Track materialized view refresh durations
  • ✅ Alert on p95 latency threshold breaches

References

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.36%
按下载量换算34

Claude

30.55%
按下载量换算28

Cursor

18.3%
按下载量换算17

Gemini CLI

9.81%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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