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java-coding-standards
Spring Boot服务的Java编码标准:命名、不可变性、Optional用法、流、异常、泛型和项目布局。
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Spring Boot服务的Java编码标准:命名、不可变性、Optional用法、流、异常、泛型和项目布局。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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| name | java-coding-standards |
| description | Spring Boot服务的Java编码标准:命名、不可变性、Optional用法、流、异常、泛型和项目布局。 |
| origin | ECC |
适用于 Spring Boot 服务中可读、可维护的 Java (17+) 代码的规范。
// PASS: Classes/Records: PascalCase
public class MarketService {}
public record Money(BigDecimal amount, Currency currency) {}
// PASS: Methods/fields: camelCase
private final MarketRepository marketRepository;
public Market findBySlug(String slug) {}
// PASS: Constants: UPPER_SNAKE_CASE
private static final int MAX_PAGE_SIZE = 100;
// PASS: Favor records and final fields
public record MarketDto(Long id, String name, MarketStatus status) {}
public class Market {
private final Long id;
private final String name;
// getters only, no setters
}
// PASS: Return Optional from find* methods
Optional<Market> market = marketRepository.findBySlug(slug);
// PASS: Map/flatMap instead of get()
return market
.map(MarketResponse::from)
.orElseThrow(() -> new EntityNotFoundException("Market not found"));
// PASS: Use streams for transformations, keep pipelines short
List<String> names = markets.stream()
.map(Market::name)
.filter(Objects::nonNull)
.toList();
// FAIL: Avoid complex nested streams; prefer loops for clarity
MarketNotFoundException)catch (Exception ex),除非在中心位置重新抛出/记录throw new MarketNotFoundException(slug);
public <T extends Identifiable> Map<Long, T> indexById(Collection<T> items) { ... }
src/main/java/com/example/app/
config/
controller/
service/
repository/
domain/
dto/
util/
src/main/resources/
application.yml
src/test/java/... (mirrors main)
private static final Logger log = LoggerFactory.getLogger(MarketService.class);
log.info("fetch_market slug={}", slug);
log.error("failed_fetch_market slug={}", slug, ex);
@Nullable;否则使用 @NonNull@NotNull, @NotBlank)记住:保持代码意图明确、类型安全且可观察。除非证明有必要,否则优先考虑可维护性而非微优化。
Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.
Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use when presenting a plan for review, or when feedback like "move this, change that" is easier pointed at than typed.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
基于本能的学习系统,通过钩子观察会话,创建带置信度评分的原子本能,并将其进化为技能/命令/代理。v2.1版本增加了项目范围的本能,以防止跨项目污染。
任意の自動コンパクションではなく、タスクフェーズを通じてコンテキストを保持するための論理的な間隔での手動コンパクションを提案します。