Performance Analyzer
CheckedAnalyzes application performance metrics to identify bottlenecks and suggest optimization strategies for improved efficiency.
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 andronics/claude-plugin-css-pro --skill performance-analyzer -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
andronics
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 andronics/claude-plugin-css-pro at 06be89aff3.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 06be89aff3
- Scanned
- 1 file, 559 lines
About this skill
What it does
The performance-analyzer skill assesses the efficiency of code snippets. It can identify bottlenecks, suggest optimizations, and provide insights into resource usage. This allows for improved application speed and reduced operational costs by pinpointing areas needing attention.
When to use it
- Debugging slow applications: Analyze specific functions or modules exhibiting poor performance.
- Optimizing critical code paths: Focus on improving the efficiency of frequently executed sections of code.
- Evaluating new algorithms: Compare the performance characteristics of different approaches before implementation.
- Identifying resource leaks: Detect areas where resources are not being released properly, leading to increased consumption.
Key capabilities
- Code analysis
- Bottleneck identification
- Optimization suggestions
- Resource usage insights
Example prompts
- "Analyze this Python code for performance bottlenecks: [code snippet]"
- "How can I optimize the execution time of this JavaScript function? [function definition]"
- "What resources is this Java class consuming?"
Tips & gotchas
The skill's effectiveness depends on providing clear and concise code snippets. It may require context or additional information about the environment in which the code runs for accurate analysis.