一键导入
verify
Run style checks and tests on changed files to verify code quality before committing.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Run style checks and tests on changed files to verify code quality before committing.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | verify |
| description | Run style checks and tests on changed files to verify code quality before committing. |
Run verification on the current changes:
Find changed files:
git diff --name-only HEAD
Also include any files you've been editing in this session.
Style check on each changed Python file or its parent directory:
python setup.py style --scope <path>
If issues are found, fix them with --fix and report what changed.
Run relevant tests based on which collection was modified:
nemo/collections/asr/ → pytest tests/collections/asr --download -m "not pleasefixme" -v --timeout=300nemo/collections/tts/ → pytest tests/collections/tts --download -m "not pleasefixme" -v --timeout=300nemo/collections/audio/ → pytest tests/collections/audio --download -m "not pleasefixme" -v --timeout=300nemo/collections/speechlm2/ → pytest tests/collections/speechlm2 -m "not pleasefixme" -v --timeout=300nemo/collections/common/ → pytest tests/collections/common -m "not pleasefixme" -v --timeout=300nemo/core/ → pytest tests/core -m "not pleasefixme" -v --timeout=300Report results: summarize passes and failures. For failures, show relevant error output and suggest fixes.
Guide NeMo Speech users through ASR fine-tuning with container setup and Lhotse training.
Get a pull request to green CI. Diagnose and fix CI failures, push fixes, re-trigger CI via the "Run CICD" label, and repeat until all checks pass. Does not post comments — this is a local developer tool.
Fix a GitHub issue in NeMo Speech (NVIDIA-NeMo/NeMo). Read the issue, reproduce the bug with a failing test, implement the fix, and verify tests pass. Only opens a PR if the user explicitly asks for it.
Debug distributed training failures (NeMo, Megatron, PyTorch) from worker stderr logs and optional AIStore daemon logs. Finds root cause across NCCL timeouts, data loading errors, and storage failures.