System Profiler
Profiles a script, process, or GPU setup and reports bottlenecks with a change log.
- Stars
- 18,482
- Licence
- MIT
- Files
- 1 file
What it does
When you ask the agent to profile something (a Python script, a running process, GPU or memory use, or a multi-GPU link), it picks suitable measurement tools, and where needed writes small timing or memory tracking code into your project. It then runs the measurements, saves outputs to a profile_output folder, and gives you tables of findings with ranked suggestions. Every file it changed for profiling is listed so you can review or remove those changes.
Great for
- Engineers trying to find why a training job or inference server is slow
- Researchers who want to see GPU, memory, or inter-GPU communication costs before scaling up
- Anyone who wants a structured bottleneck report rather than raw tool output
Skip it if
- Quick one-line checks where a single tool command is enough, since the skill adds a full workflow with code edits
- Production systems where running profilers or inserting instrumentation could disrupt live traffic or change timing behaviour
- Projects where the agent should not modify source files, because the skill explicitly allows inline edits to your code
Try asking
- “Profile train.py and tell me where the time goes”
- “Find the bottleneck in my vllm serving setup”
- “Check GPU memory usage and whether data is duplicated between CPU and GPU”
- “Benchmark the NCCL communication in my multi-GPU training run”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
system-profile.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip system-profile.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip system-profile.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Name a specific target such as a script path, PID, or 'gpu' to get focused results instead of a broad sweep
- Review the instrumentation changelog before accepting results, and ask the agent to clean up inserted code afterwards
- Run profiling on a representative workload in a test environment rather than production
What's inside
- SKILL.md
Redistributed unmodified from wanshuiyin/Auto-claude-code-research-in-sleep under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.