菜单
Generate a local phyai environment report for debugging system, Python, CUDA/GPU, dependency, workspace package, git, and PHYAI_* configuration issues. Use when asked to inspect, summarize, export, or diagnose the current phyai development/runtime environment.
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
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.
去除文本中的 AI 生成痕迹。适用于编辑或审阅文本，使其听起来更自然、更像人类书写。 基于维基百科的"AI 写作特征"综合指南。检测并修复以下模式：夸大的象征意义、 宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、 AI 词汇、否定式排比、过多的连接性短语。
Use this skill when implementing, porting, integrating, reproducing, or debugging support for a model in PHYAI. This includes translating architecture research into PHYAI code, adding model configuration, modeling modules, runners, schedulers, weight loading, layer reuse, focused tests, validation scripts, and implementation plans while respecting PHYAI model-development constraints.
Analyze a phyai .memory file or directory supplied by the user: parse what task/session it records, locate and inspect the referenced code repository when available, verify claims against local code and git history, and explain what the memory did, changed, validated, and left unresolved.
Use this skill when the user provides a paper, arXiv link, technical report, model card, checkpoint name, GitHub repository, or local codebase and asks to research, explain, compare, or implement a model architecture. This skill guides architecture research for PHYAI: source collection, paper/code tracing, module decomposition, tensor shape analysis, dependency mapping, and implementation-oriented reporting.
Triage and resolve review comments on a GitHub PR — fetch all comment surfaces (issue / inline / review), validate each suggestion against upstream source rather than trusting blindly, present findings to the user before editing, then make focused changes and re-run tests. Use when the user asks to "check PR N's comments", "address review feedback", "resolve PR comments", or similar.
| name | phyai-local-env-report |
| description | Generate a local phyai environment report for debugging system, Python, CUDA/GPU, dependency, workspace package, git, and PHYAI_* configuration issues. Use when asked to inspect, summarize, export, or diagnose the current phyai development/runtime environment. |
Use this skill to produce a reproducible local environment report for the
phyai monorepo. Prefer the bundled script over ad hoc command collection.
From the repository root:
uv run python .claude/skills/phyai-local-env-report/scripts/collect_env_report.py
To save a report:
uv run python .claude/skills/phyai-local-env-report/scripts/collect_env_report.py --output reports/local-env.md
If uv is unavailable, run the same script with the active Python:
python .claude/skills/phyai-local-env-report/scripts/collect_env_report.py
phyai repository root unless the user explicitly
names another checkout.--output is used, or summarize the most relevant
findings from stdout.DiagnosticsCUDA / GPUPython Packagesphyai Runtime Environmentuv run python .claude/skills/phyai-local-env-report/scripts/collect_env_report.py --help
Common options:
--output PATH: write the Markdown or JSON report to a file.--format markdown|json: choose the output format; Markdown is default.--no-gpu-detail: skip slower GPU detail commands such as
nvidia-smi topo -m.The script captures:
PHYAI_* env vars from phyai.env plus extra process-level
PHYAI_* variables used elsewhere in the codebase;phyai-kernel show-env output when available.