菜单
Code review skill specialized for tt-xla (Python + C++ PJRT plugin for Tenstorrent hardware). Covers C++ memory safety, PJRT API patterns, Python test standards, and project-specific conventions.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
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。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/tenstorrent/tt-xla --skill code-reviewer命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | code-reviewer |
| description | Code review skill specialized for tt-xla (Python + C++ PJRT plugin for Tenstorrent hardware). Covers C++ memory safety, PJRT API patterns, Python test standards, and project-specific conventions. |
Specialized code review toolkit for the tt-xla project: a PJRT-based backend that enables JAX and PyTorch/XLA on Tenstorrent AI hardware.
Languages: C++20, Python 3.12
Build: CMake + Ninja, Python setuptools (wheel packaging)
Formatting: clang-format (C++, style from .clang-format), black + isort (Python)
Testing: pytest with custom markers
Logging: loguru (C++), Python stdlib logging
CI: pre-commit hooks (black, clang-format, SPDX copyright, trailing whitespace, isort)
When invoked via /code-reviewer, Claude Code loads this file and the reference documents into context, then applies them to review the code. No external tools, containers, or scripts needed.
references/code_review_checklist.mdreferences/coding_standards.mdreferences/common_antipatterns.mdAll review focus areas, coding standards, and antipatterns are documented in the reference files below. Refer to these as the single source of truth during reviews:
references/code_review_checklist.md — Step-by-step review checklist (C++, Python, CMake, general)references/coding_standards.md — Project coding standards for C++ and Pythonreferences/common_antipatterns.md — Antipatterns specific to tt-xla with wrong/right examples