cuda-debugging
Expert skill for GPU debugging using CUDA-GDB and NVIDIA Compute Sanitizer. Detect memory errors, race conditions, uninitialized memory access, validate atomic operations, analyze kernel synchronization issues, and generate debugging reports with recommendations.
npx skills add a5c-ai/babysitter --skill cuda-debugging --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.
# cuda-debugging You are **cuda-debugging** - a specialized skill for GPU debugging and error detection using NVIDIA's Compute Sanitizer and CUDA-GDB tools. This skill provides expert capabilities for identifying and resolving correctness issues in CUDA programs. ## Overview This skill enables AI-powered GPU debugging operations including: - Executing compute-sanitizer memory checks (memcheck) - Detecting race conditions with racecheck tool - Identifying memory leaks and invalid accesses - Using CUDA-GDB for kernel debugging - Analyzing kernel synchronization issues - Validating atomic operation correctness - Detecting uninitialized memory access (initcheck) - Generating debugging reports with actionable recommendations ## Prerequisites - NVIDIA CUDA Toolkit 11.0+ with compute-sanitizer - CUDA-GDB for interactive debugging - GPU with debugging support (compute capability 3.5+) - Debug build of CUDA application (-G -lineinfo flags) - Optional: Nsight Visual Studio Code Extension ## Capabilities ### 1. Memory Error Detection (Memcheck) Detect memory access errors and leaks: ```bash # Basic memory check compute-sanitizer --tool memcheck ./cuda_program # With detailed error reporting c
- Overview
- Prerequisites
- Capabilities
- 1. Memory Error Detection (Memcheck)
- 2. Race Condition Detection (Racecheck)
- 3. Uninitialized Memory Detection (Initcheck)
- 4. Synchronization Validation (Synccheck)
- 5. CUDA-GDB Debugging Commands
- 6. Common Debugging Patterns
- 7. Error Code Handling
- 8. Debugging Report Generation
- MCP Server Integration
- Best Practices
- Debugging Build Configuration
Basic memory check compute-sanitizer --tool memcheck ./cuda_program With detailed error reporting compute-sanitizer --tool memcheck --report-api-errors all ./cuda_program Log errors to file compute-sanitizer --tool memcheck --log-file memcheck.log ./cuda_program Check for memory leaks compute-sanitizer --tool memcheck --leak-check full ./cuda_program Track allocations compute-sanitizer --tool memcheck --track-alloc-dealloc yes ./cuda_program
What does the cuda-debugging skill do?
Expert skill for GPU debugging using CUDA-GDB and NVIDIA Compute Sanitizer. Detect memory errors, race conditions, uninitialized memory access, validate atomic operations, analyze kernel synchronization issues, and generate debugging reports with recommendations.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill cuda-debugging --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 a5c-ai/babysitter, a repository with 1,642 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.