LLM Pipeline Profiler Analysis
BBuf/AI-Infra-Auto-Driven-SKILLS
Breaks LLM torch profiler traces down by forward pass, layer and kernel, with timing tables and Perfetto time ranges for the layers you want to inspect.
Agent skill
by ascend-ai-coding in ascend-ai-coding/awesome-ascend-skills
昇腾 NPU 平台 vLLM 大模型推理服务一键部署。触发:用户说'部署 模型名'、'NPU 部署模型'、'vllm serve'。流程:SSH检查 → NPU检查 → 配置发现(必须验证) → 用户确认 → 部署 → cron监控 → 验证。约束:(1) 配置必须从官方文档验证,禁止猜测;(2) 后台启动必须用cron监控,禁止手动轮询。支持…
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deploy --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .claude/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .claude/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deployType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deploy --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .agents/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .agents/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deploy --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .cursor/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .cursor/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ascend-ai-coding/awesome-ascend-skills.git --path external/gitcode-ascend/vllm-ascend-deploy--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deploy --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .gemini/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .gemini/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deployInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .github/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .github/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills external-gitcode-ascend-vllm-ascend-deploy --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/external/gitcode-ascend/vllm-ascend-deploy .opencode/skills/external-gitcode-ascend-vllm-ascend-deploy && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "external-gitcode-ascend-vllm-ascend-deploy" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/external/gitcode-ascend/vllm-ascend-deploy into .opencode/skills/external-gitcode-ascend-vllm-ascend-deploy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "external-gitcode-ascend-vllm-ascend-deploy", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
external-gitcode-ascend-vllm-ascend-deploy昇腾 NPU 平台 vLLM 大模型推理服务一键部署。触发:用户说'部署 模型名'、'NPU 部署模型'、'vllm serve'。流程:SSH检查 → NPU检查 → 配置发现(必须验证) → 用户确认 → 部署 → cron监控 → 验证。约束:(1) 配置必须从官方文档验证,禁止猜测;(2) 后台启动必须用cron监控,禁止手动轮询。支持…
External Gitcode Ascend Vllm Ascend Deploy is an agent skill from ascend-ai-coding/awesome-ascend-skills. 昇腾 NPU 平台 vLLM 大模型推理服务一键部署。触发:用户说'部署 模型名'、'NPU 部署模型'、'vllm serve'。流程:SSH检查 → NPU检查 → 配置发现(必须验证) → 用户确认 → 部署 → cron监控 → 验证。约束:(1) 配置必须从官方文档验证,禁止猜测;(2) 后台启动必须用cron监控,禁止手动轮询。支持 Qwen/Qwen3.5、GLM、DeepSeek、Kimi。
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/deployment-procedure.md`, `references/model-discovery.md` and `references/troubleshooting.md`).
It sits in AI & LLM Engineering, covering LLM inference and serving and Scheduled and recurring tasks. It works with vLLM, Qwen, DeepSeek and Kimi. The repository describes itself as: A comprehensive knowledge base for Huawei Ascend NPU development, structured as distributed Agent Skills. https://ascend-ai-coding.github.io/awesome-ascend-skills/.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 62a4ecb. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (Shell and Python), which the agent can run.
Shell commands in SKILL.md call:
curlsshdockerbashpythonFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
gitcode.comdocs.vllm.aimodelers.cnFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
External Gitcode Ascend Vllm Ascend Deploy loads about 1.2k tokens when it runs, and up to ~5k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 255 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
Without a licence we can't republish the file, so here is its outline and opening line. It has 255 words (~1,203 tokens).
SKILL.md and 7 other files (scripts, references) in external/gitcode-ascend/vllm-ascend-deploy of ascend-ai-coding/awesome-ascend-skills.
Open the folder on GitHubat commit 62a4ecb
External Gitcode Ascend Vllm Ascend Deploy next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| External Gitcode Ascend Vllm Ascend Deploy this skillascend-ai-coding/awesome-ascend-skills | 174 | — | ~1.2k | Automated safety check: Pass | None | |
| LLM Pipeline Profiler AnalysisBBuf/AI-Infra-Auto-Driven-SKILLS | 900 | — | ~3.9k | Automated safety check: Pass | None | |
| Add Modelguoqingbao/xinfer | 333 | — | ~4.2k | Automated safety check: Notes | MIT | |
| Serving LLMs On Instinctamd/skills | 395 | — | ~4k | Automated safety check: Notes | MIT | |
| Update Ollama Cloud Modelsheypinchy/pinchy | 182 | — | ~3.9k | Automated safety check: Notes | AGPL-3.0 | |
| Dpskv3 Logistic Reviewmirage-project/mirage | 2.5k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 |
BBuf/AI-Infra-Auto-Driven-SKILLS
Breaks LLM torch profiler traces down by forward pass, layer and kernel, with timing tables and Perfetto time ranges for the layers you want to inspect.
guoqingbao/xinfer
Adapt and port new LLM model architectures to this xinfer project.
amd/skills
Serves AI models on AMD Instinct GPU hardware using vLLM. An agent skill from amd/skills.
heypinchy/pinchy
A skill your agent uses when a new Ollama Cloud model is announced or available (e.g.
mirage-project/mirage
Audit the DeepSeek V3 MPK demo + builder chain end-to-end and confirm logical equivalence with vLLM's reference implementation.
majiayu000/claude-skill-registry
vLLM is a high-throughput inference and serving engine for large language models that exposes an OpenAI-compatible HTTP API and a Python batch API.
ascend-ai-coding/awesome-ascend-skills
当用户需要对华为昇腾 NPU 进行硬件层面的管理、测试或诊断时使用此 skill。典型场景: - 查看 NPU 卡的状态、温度、利用率 - 测试内存带宽(h2d/d2h/d2d/p2p) - 跑算力/功耗基准测试(TFLOPS、TOPS) - 诊断 NPU 硬件故障或做健康检查 - 对 NPU 卡做压力测试(aicore、内存) - 复位/恢复卡住或异常的 NPU 卡 典型用户问题(即使不提…
ascend-ai-coding/awesome-ascend-skills
End-to-end AscendC custom operator development for Ascend NPU in an ascend-kernel (csrc/ops + build.sh + torchnpu PyTorch custom op) project.
ascend-ai-coding/awesome-ascend-skills
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation.
ascend-ai-coding/awesome-ascend-skills
当需要编写 PyPTO 算子实现时使用此 skill。基于需求规格、设计方案和参考实现,生成完整可运行的 PyPTO 算子实现与配套测试、文档。Triggers: 实现算子、写 kernel、编写实现、写 impl、算子编码、开始编码、code the op、写 test、生成测试、写实现代码、op develop、kernel 实现。
ascend-ai-coding/awesome-ascend-skills
Analyze official Megatron-LM commits, PRs, and branch change sets to identify feature evolution, candidate breaking changes, and migration-relevant events.
ascend-ai-coding/awesome-ascend-skills
Track and normalize change requests against the official Megatron-LM repository by branch, PR, commit, commit range, or time window.
Categories
昇腾 NPU 平台 vLLM 大模型推理服务一键部署。触发:用户说'部署 模型名'、'NPU 部署模型'、'vllm serve'。流程:SSH检查 → NPU检查 → 配置发现(必须验证) → 用户确认 → 部署 → cron监控 → 验证。约束:(1) 配置必须从官方文档验证,禁止猜测;(2) 后台启动必须用cron监控,禁止手动轮询。支持…. External Gitcode Ascend Vllm Ascend Deploy is an agent skill from ascend-ai-coding/awesome-ascend-skills.
External Gitcode Ascend Vllm Ascend Deploy fits situations like: tasks that involve LLM inference and serving; tasks that involve Scheduled and recurring tasks.
Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a claude-code`. Or copy the skill folder (external/gitcode-ascend/vllm-ascend-deploy in ascend-ai-coding/awesome-ascend-skills) into .claude/skills/external-gitcode-ascend-vllm-ascend-deploy in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a codex`. Or copy the skill folder (external/gitcode-ascend/vllm-ascend-deploy in ascend-ai-coding/awesome-ascend-skills) into .agents/skills/external-gitcode-ascend-vllm-ascend-deploy in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill external-gitcode-ascend-vllm-ascend-deploy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/external-gitcode-ascend-vllm-ascend-deploy, .gemini/skills/external-gitcode-ascend-vllm-ascend-deploy, .github/skills/external-gitcode-ascend-vllm-ascend-deploy and .opencode/skills/external-gitcode-ascend-vllm-ascend-deploy in your project.
Going by SKILL.md and its folder, External Gitcode Ascend Vllm Ascend Deploy needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (curl, ssh, docker, bash and python). Our summary lists: Python 3; A Bash shell; Docker.
SKILL.md names 3 domains. As links in the text: gitcode.com, docs.vllm.ai and modelers.cn. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
No licence was found for External Gitcode Ascend Vllm Ascend Deploy or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.7k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with External Gitcode Ascend Vllm Ascend Deploy: LLM Pipeline Profiler Analysis (BBuf/AI-Infra-Auto-Driven-SKILLS, 900 stars), Add Model (guoqingbao/xinfer, 333 stars), Serving LLMs On Instinct (amd/skills, 395 stars) and Update Ollama Cloud Models (heypinchy/pinchy, 182 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ascend-ai-coding (a GitHub organization) maintains it in ascend-ai-coding/awesome-ascend-skills, which has 174 GitHub stars. The repository holds 69 skills in this directory. The repository was last updated on October 7, 2026.
Source: ascend-ai-coding/awesome-ascend-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.