Best use case
code-profiler is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Profile code performance and identify bottlenecks
Teams using code-profiler should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/code-profiler/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How code-profiler Compares
| Feature / Agent | code-profiler | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Profile code performance and identify bottlenecks
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Code Profiler Skill
## Purpose
Profile algorithm implementations to identify performance bottlenecks and optimization opportunities.
## Capabilities
- Runtime profiling
- Memory profiling
- Cache miss analysis
- Hot spot identification
- Optimization suggestions
- Comparative benchmarking
## Target Processes
- code-level-optimization
- complexity-optimization
- memory-optimization
## Profiling Dimensions
### Time Profiling
- Function-level timing
- Line-by-line profiling
- Call graph analysis
- Hot spot detection
### Memory Profiling
- Heap allocation tracking
- Memory leak detection
- Peak memory usage
- Allocation patterns
### Cache Analysis
- Cache miss rates
- Memory access patterns
- Data locality issues
## Input Schema
```json
{
"type": "object",
"properties": {
"code": { "type": "string" },
"language": { "type": "string" },
"profileType": {
"type": "string",
"enum": ["time", "memory", "cache", "all"]
},
"testInput": { "type": "string" },
"iterations": { "type": "integer", "default": 1 }
},
"required": ["code", "profileType"]
}
```
## Output Schema
```json
{
"type": "object",
"properties": {
"success": { "type": "boolean" },
"timing": { "type": "object" },
"memory": { "type": "object" },
"hotSpots": { "type": "array" },
"recommendations": { "type": "array" }
},
"required": ["success"]
}
```
## Integration
Can integrate with profiling tools like gprof, perf, Valgrind, cProfile, and language-specific profilers.Related Skills
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