Creating Description For Gh PR
redis/jedis
Generate a clear, concise GitHub PR title and description from the diff between two local git branches, and save it to prDescription.md in the repo root.
Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation.
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install decebals/claude-code-java performance-smell-detection --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performance-smell-detection .claude/skills/performance-smell-detection && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .claude/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install decebals/claude-code-java performance-smell-detection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/performance-smell-detection .agents/skills/performance-smell-detection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .agents/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install decebals/claude-code-java performance-smell-detection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/performance-smell-detection .cursor/skills/performance-smell-detection && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .cursor/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/decebals/claude-code-java.git --path skills/performance-smell-detection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install decebals/claude-code-java performance-smell-detection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/performance-smell-detection .gemini/skills/performance-smell-detection && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .gemini/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install decebals/claude-code-java performance-smell-detectionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/performance-smell-detection .github/skills/performance-smell-detection && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .github/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install decebals/claude-code-java performance-smell-detection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/decebals/claude-code-java.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/performance-smell-detection .opencode/skills/performance-smell-detection && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "performance-smell-detection" agent skill from https://github.com/decebals/claude-code-java/tree/main/skills/performance-smell-detection into .opencode/skills/performance-smell-detection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-smell-detection", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
performance-smell-detectionDetect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation.
Performance Smell Detection is an agent skill from decebals/claude-code-java. Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation. Provides awareness, not absolutes - always measure before optimizing. For JPA/database performance, use jpa-patterns instead.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `README.md`).
It sits in Development. It works with Java. The repository describes itself as: Reusable AI development infrastructure for Java projects, optimized for Claude Code. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 0d98fe9. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are java and bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Performance Smell Detection loads about 2.3k tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 477 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from decebals/claude-code-java at commit 0d98fe9, republished under its MIT licence (© decebals). 477 words, ~2,270 tokens.
.claude/skills/performance-smell-detection/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Identify potential code-level performance issues in Java code.
"Premature optimization is the root of all evil" - Donald Knuth
This skill helps you notice potential performance smells, not blindly "fix" them. Modern JVMs (Java 21/25) are highly optimized. Always:
This skill: Code-level performance (streams, collections, objects)
For database: Use jpa-patterns skill (N+1, lazy loading, pagination)
For architecture: Use architecture-review skill
| Smell | Severity | Context |
|---|---|---|
| Regex compile in loop | 🔴 High | Always worth fixing |
| String concat in loop | 🟡 Medium | Still valid in Java 21/25 |
| Stream in tight loop | 🟡 Medium | Depends on collection size |
| Boxing in hot path | 🟡 Medium | Measure first |
| Unbounded collection | 🔴 High | Memory risk |
| Missing collection capacity | 🟢 Low | Minor, measure if critical |
Since Java 9 (JEP 280), string concatenation with + uses invokedynamic, not StringBuilder. The JVM optimizes simple concatenation well.
Java 25 adds String::hashCode constant folding for additional optimization in Map lookups with String keys.
// 🔴 Still problematic - new String each iteration
String result = "";
for (String s : items) {
result += s; // O(n²) - creates n strings
}
// ✅ StringBuilder for loops
StringBuilder sb = new StringBuilder();
for (String s : items) {
sb.append(s);
}
String result = sb.toString();
// ✅ Or use String.join / Collectors.joining
String result = String.join("", items);// ✅ Fine in Java 9+ - JVM optimizes this
String message = "User " + name + " logged in at " + timestamp;
// ✅ Also fine
return "Error: " + code + " - " + description;// 🟡 String.format has parsing overhead
log.debug(String.format("Processing %s with id %d", name, id));
// ✅ Parameterized logging (SLF4J)
log.debug("Processing {} with id {}", name, id);Streams have overhead, but it's often acceptable:
Recommendation: Prefer streams for readability. Optimize to loops only when profiling shows a bottleneck.
// 🔴 Stream created per iteration in hot loop
for (int i = 0; i < 1_000_000; i++) {
boolean found = items.stream()
.anyMatch(item -> item.getId() == i);
}
// ✅ Pre-compute lookup structure
Set<Integer> itemIds = items.stream()
.map(Item::getId)
.collect(Collectors.toSet());
for (int i = 0; i < 1_000_000; i++) {
boolean found = itemIds.contains(i);
}// ✅ Single pass, readable, not in tight loop
List<String> names = users.stream()
.filter(User::isActive)
.map(User::getName)
.sorted()
.collect(Collectors.toList());
// ✅ Primitive streams avoid boxing
int sum = numbers.stream()
.mapToInt(Integer::intValue)
.sum();// 🔴 Parallel on small collection - overhead > benefit
smallList.parallelStream().map(...); // < 10K items
// 🔴 Parallel with shared mutable state
List<String> results = new ArrayList<>();
items.parallelStream()
.forEach(results::add); // Race condition!
// ✅ Parallel for CPU-intensive + large collections
List<Result> results = largeDataset.parallelStream() // > 10K items
.map(this::expensiveCpuComputation)
.collect(Collectors.toList());Boxing creates objects on heap, adds GC pressure. JVM caches small values (-128 to 127) but not larger ones.
Future: Project Valhalla will improve this significantly.
// 🔴 Boxing in tight loop - creates millions of objects
Long sum = 0L;
for (int i = 0; i < 1_000_000; i++) {
sum += i; // Unbox, add, box
}
// ✅ Primitive
long sum = 0L;
for (int i = 0; i < 1_000_000; i++) {
sum += i;
}// 🟡 Boxing overhead
int sum = list.stream()
.reduce(0, Integer::sum);
// ✅ Primitive stream
int sum = list.stream()
.mapToInt(Integer::intValue)
.sum();This advice is not outdated - Pattern.compile is expensive.
// 🔴 Compiles pattern every iteration
for (String input : inputs) {
if (input.matches("\\d{3}-\\d{4}")) { // Compiles regex!
process(input);
}
}
// ✅ Pre-compile
private static final Pattern PHONE = Pattern.compile("\\d{3}-\\d{4}");
for (String input : inputs) {
if (PHONE.matcher(input).matches()) {
process(input);
}
}// 🟢 Low severity - but free optimization if size known
List<User> users = new ArrayList<>(expectedSize);
Map<String, User> map = new HashMap<>(expectedSize * 4 / 3 + 1);// 🟡 O(n) lookup in loop
List<String> allowed = getAllowed();
for (Request r : requests) {
if (allowed.contains(r.getId())) { } // O(n) each time
}
// ✅ O(1) lookup
Set<String> allowed = new HashSet<>(getAllowed());
for (Request r : requests) {
if (allowed.contains(r.getId())) { } // O(1)
}// 🔴 Memory risk - could grow unbounded
@GetMapping("/users")
public List<User> getAllUsers() {
return userRepository.findAll(); // Millions of rows?
}
// ✅ Pagination
@GetMapping("/users")
public Page<User> getUsers(Pageable pageable) {
return userRepository.findAll(pageable);
}// 🟡 Traditional thread pool for I/O - wastes OS threads
ExecutorService executor = Executors.newFixedThreadPool(100);
for (Request request : requests) {
executor.submit(() -> callExternalApi(request)); // Blocks OS thread
}
// ✅ Virtual threads - millions of concurrent I/O operations
try (ExecutorService executor = Executors.newVirtualThreadPerTaskExecutor()) {
for (Request request : requests) {
executor.submit(() -> callExternalApi(request));
}
}// ✅ Structured concurrency for parallel I/O
try (StructuredTaskScope.ShutdownOnFailure scope = new StructuredTaskScope.ShutdownOnFailure()) {
Future<User> user = scope.fork(() -> fetchUser(id));
Future<Orders> orders = scope.fork(() -> fetchOrders(id));
scope.join();
scope.throwIfFailed();
return new UserProfile(user.resultNow(), orders.resultNow());
}# Find regex in loops (potential compile overhead)
grep -rn "\.matches(\|\.split(" --include="*.java"
# Find potential boxing (Long/Integer as variables)
grep -rn "Long\s\|Integer\s\|Double\s" --include="*.java" | grep "= 0\|+="
# Find ArrayList without capacity
grep -rn "new ArrayList<>()" --include="*.java"
# Find findAll without pagination
grep -rn "findAll()" --include="*.java"© decebals, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/performance-smell-detection of decebals/claude-code-java.
Open the folder on GitHubat commit 0d98fe9
Performance Smell Detection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Performance Smell Detection this skilldecebals/claude-code-java | 751 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Creating Description For Gh PRredis/jedis | 12k | — | ~838 | Automated safety check: Pass | MIT | |
| Code Review Skillawesome-skills/code-review-skill | 2.1k | — | ~2.8k | Automated safety check: Notes | MIT | |
| Caffeine Cache Optimization Experimentsben-manes/caffeine | 18k | — | ~2.6k | Automated safety check: Notes | Apache-2.0 | |
| Coding Standardsapache/shardingsphere | 21k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Git History Bug Auditben-manes/caffeine | 18k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 |
redis/jedis
Generate a clear, concise GitHub PR title and description from the diff between two local git branches, and save it to prDescription.md in the repo root.
awesome-skills/code-review-skill
Provides comprehensive code review guidance for React 19, Vue 3, Angular 17+, Svelte 5, Rust, TypeScript, Java, Java 8, PHP, Ruby, Rails, Python, Django, FastAPI, Go, C/.NET, Kotlin, Swift, Dart…
ben-manes/caffeine
Runs controlled JMH experiments on the Caffeine cache to find shared contention and hot-path waste, then reviews correctness and returns a reviewable patch.
apache/shardingsphere
Apply Apache ShardingSphere's written coding standards when explicitly requested, or when code-implementation routes task-changed production, test, script, build, generated, or Maven POM artifacts…
ben-manes/caffeine
Audits a module by walking its git history commit by commit, tracking unresolved issues forward, and reporting the ones that survive to HEAD as findings.
chewiebug/GCViewer
Run the full build-and-deploy.yaml workflow locally via act + Docker.
decebals/claude-code-java
A practical Java reference for Builder, Factory, Singleton, Strategy, Observer and other patterns, with a table matching problems to patterns.
decebals/claude-code-java
JPA/Hibernate patterns and common pitfalls (N+1, lazy loading, transactions, queries).
decebals/claude-code-java
Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing.
decebals/claude-code-java
Reviews REST API design for correct HTTP verbs, versioning, DTO use, consistent responses and backward compatibility before an API change ships.
decebals/claude-code-java
Reviews a Java project's architecture at the macro level: package structure, module boundaries, dependency direction and layering.
decebals/claude-code-java
Builds changelog entries from conventional commits in a Java project, after working out whether it uses SemVer, two-part versions or calendar versions.
Works with
Categories
Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation. Performance Smell Detection is an agent skill from decebals/claude-code-java. Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation.
Performance Smell Detection fits situations like: development work in your project.
Run `npx skills add decebals/claude-code-java --skill performance-smell-detection -a claude-code`. Or copy the skill folder (skills/performance-smell-detection in decebals/claude-code-java) into .claude/skills/performance-smell-detection in your project. Claude Code loads it when a task matches its description.
Run `npx skills add decebals/claude-code-java --skill performance-smell-detection -a codex`. Or copy the skill folder (skills/performance-smell-detection in decebals/claude-code-java) into .agents/skills/performance-smell-detection in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add decebals/claude-code-java --skill performance-smell-detection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performance-smell-detection, .gemini/skills/performance-smell-detection, .github/skills/performance-smell-detection and .opencode/skills/performance-smell-detection in your project.
SKILL.md names no scripts, command-line tools or credentials: Performance Smell Detection is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Performance Smell Detection is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Performance Smell Detection: Creating Description For Gh PR (redis/jedis, 12k stars), Code Review Skill (awesome-skills/code-review-skill, 2.1k stars), Caffeine Cache Optimization Experiments (ben-manes/caffeine, 18k stars) and Coding Standards (apache/shardingsphere, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
decebals (a GitHub user) maintains it in decebals/claude-code-java, which has 751 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on September 6, 2026.
Source: decebals/claude-code-java on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.