AB nvidia-cuda
Use when work targets NVIDIA GPUs for deep learning training, inference, distributed execution, CUDA/Triton kernels, or AI infra tuning. Enforces GPU-aware code conventions for PyTorch on CUDA, including dtype policy, memory movement, NCCL/DDP/FSDP choices, profiling, benchmarking, and H100/H200/B200 optimization habits.
As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, progress reporting
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 22. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5688 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 70/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python, node) that frontmatter does not declare
- 70Execution cost. Instruction body is 5688 tokens
- 85Steps. 307 steps, 1 vague phrases
- 100Result and completion. Output format and completion criterion are stated
- 100Failures and branches. 14 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- low 21 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 322: enough signal without eating the budget
- +4Structure: 38 headings
- +3Step-by-step instructions: 307 items
- +3Output format is stated explicitly
- +4Reference files are cited in the instructions (2 of 3)
- +3All 7 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.