performance-profiling
Identify computational bottlenecks, analyze scaling behavior, estimate memory requirements, and receive optimization recommendations for any computational simulation. Use when simulations are slow, investigating parallel efficiency, planning resource allocation, or seeking performance improvements through timing analysis, scaling studies, memory profiling, or bottleneck detection.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill performance-profiling --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Performance Profiling ## Goal Provide tools to analyze simulation performance, identify bottlenecks, and recommend optimization strategies for computational materials science simulations. ## Requirements - Python 3.8+ - No external dependencies (uses Python standard library only) - Works on Linux, macOS, and Windows ## Inputs to Gather Before running profiling scripts, collect from the user: | Input | Description | Example | |-------|-------------|---------| | Simulation log | Log file with timing information | `simulation.log` | | Scaling data | JSON with multi-run performance data | `scaling_data.json` | | Simulation parameters | JSON with mesh, fields, solver config | `params.json` | | Available memory | System memory in GB (optional) | `16.0` | ## Decision Guidance ### When to Use Each Script ``` Need to identify slow phases? ├── YES → Use timing_analyzer.py │ └── Parse simulation logs for timing data │ Need to understand parallel performance? ├── YES → Use scaling_analyzer.py │ └── Analyze strong or weak scaling efficiency │ Need to estimate memory requirements? ├── YES → Use memory_profiler.py │ └── Estimate memory from problem parameters │ Need optimization recommendations
- Goal
- Requirements
- Inputs to Gather
- Decision Guidance
- When to Use Each Script
- Choosing Analysis Thresholds
- Script Outputs (JSON Fields)
- Workflow
- Complete Profiling Workflow
- Quick Profiling (Timing Only)
- CLI Examples
- Timing Analysis
- Scaling Analysis
- Memory Profiling
Basic timing analysis python3 scripts/timing_analyzer.py \ Custom timing pattern Strong scaling (fixed problem size) python3 scripts/scaling_analyzer.py \ Weak scaling (constant work per processor) Estimate memory requirements python3 scripts/memory_profiler.py \ Detect bottlenecks from timing only python3 scripts/bottleneck_detector.py \
What does the performance-profiling skill do?
Identify computational bottlenecks, analyze scaling behavior, estimate memory requirements, and receive optimization recommendations for any computational simulation. Use when simulations are slow, investigating parallel efficiency, planning resource allocation, or seeking performance improvements through timing analysis, scaling studies, memory profiling, or bottleneck detection.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill performance-profiling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.