Performance Smell Detection
CheckedIdentifies code inefficiencies, potential bugs, and suboptimal patterns within software projects using advanced analysis techniques.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add decebals/claude-code-java --skill performance-smell-detection -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
decebals
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned decebals/claude-code-java at 0d98fe9bd6.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 0d98fe9bd6
- Scanned
- 2 files, 399 lines
About this skill
What it does
This skill identifies potential performance bottlenecks and inefficiencies in Java code. It analyzes code for common "smells" that often indicate areas where optimization is needed, such as excessive object creation or inefficient data structures. The tool aims to provide suggestions for improving the runtime performance of Java applications.
When to use it
- Code Review: Integrate into a code review process to proactively identify and address potential performance issues before deployment.
- Performance Tuning: Use when attempting to optimize an existing application that is exhibiting slow response times or high resource consumption.
- Refactoring: Apply during refactoring efforts to ensure that changes don't inadvertently introduce new performance bottlenecks.
- Learning & Education: Help developers learn about common Java performance pitfalls and best practices.
Key capabilities
- Identifies code smells related to performance.
- Provides suggestions for optimization.
- Supports analysis of existing Java codebases.
Example prompts
- "Analyze this Java code snippet for potential performance issues: [code snippet]"
- "Can you identify any areas in this function that could be optimized for speed? [function definition]"
- "Find performance smells in the
OrderProcessingServiceclass."
Tips & gotchas
The skill's effectiveness depends on providing clear and complete code snippets or references to specific files. It is a diagnostic tool, and requires developer expertise to interpret results and implement suggested changes.