Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
MindSpeed-MM skill router and model index for Huawei Ascend NPU.
Install Mindspeed Mm Pipeline
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill mindspeed-mm-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills mindspeed-mm-pipeline --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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .claude/skills/mindspeed-mm-pipeline && 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 "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .claude/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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/skills/training/mindspeed-mm/mindspeed-mm-pipelineType 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 mindspeed-mm-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills mindspeed-mm-pipeline --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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .agents/skills/mindspeed-mm-pipeline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .agents/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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 mindspeed-mm-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills mindspeed-mm-pipeline --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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .cursor/skills/mindspeed-mm-pipeline && 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 "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .cursor/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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 skills/training/mindspeed-mm/mindspeed-mm-pipeline--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 mindspeed-mm-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ascend-ai-coding/awesome-ascend-skills mindspeed-mm-pipeline --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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .gemini/skills/mindspeed-mm-pipeline && 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 "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .gemini/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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 mindspeed-mm-pipelineInstalls 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 mindspeed-mm-pipeline -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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .github/skills/mindspeed-mm-pipeline && 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 "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .github/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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 mindspeed-mm-pipeline -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 mindspeed-mm-pipeline --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/skills/training/mindspeed-mm/mindspeed-mm-pipeline .opencode/skills/mindspeed-mm-pipeline && 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 "mindspeed-mm-pipeline" agent skill from https://github.com/ascend-ai-coding/awesome-ascend-skills/tree/main/skills/training/mindspeed-mm/mindspeed-mm-pipeline into .opencode/skills/mindspeed-mm-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mindspeed-mm-pipeline", 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.
Facts
- Skill name
mindspeed-mm-pipeline- GitHub stars
- 174
- Token cost
- ~3.5k tokens
- SKILL.md length
- 1,050 words
- Files
- 3 (incl. references)
- Skills in repo
- 70
- Repo updated
- First seen
- Licence
- None found
At a glance
MindSpeed-MM skill router and model index for Huawei Ascend NPU.
- Works in 3 steps: Megatron-based unified entry:… → Megatron-based model-specific entry:… → FSDP2-based entry:…
- The user is uncertain which MindSpeed-MM skill to use
- SKILL.md covers Model Type Router, Complete Workflow Overview, Full Model Index and Entry Script Selection Rules, plus 7 more sections
- Calls python and pip
What it does
Mindspeed Mm Pipeline is an agent skill from ascend-ai-coding/awesome-ascend-skills. MindSpeed-MM skill router and model index for Huawei Ascend NPU. Use when the user is uncertain which MindSpeed-MM skill to use, needs to choose between understanding/generative/omni/audio model categories, or wants an overview of the full training pipeline. Routes to the appropriate leaf skill based on model type.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/common-args.md` and `references/model-registry.md`).
It sits in AI & LLM Engineering. 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/.
When your agent uses it
- The user is uncertain which MindSpeed-MM skill to use
- Needs to choose between understanding/generative/omni/audio model categories
- Wants an overview of the full training pipeline
Example prompts
- “/mindspeed-mm-pipeline”
Requirements
- Python 3
- Docker
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Megatron-based unified entry: pretrain_vlm.py (VLM), pretrain_sora.py (generative) — most models use these
- Megatron-based model-specific entry: pretrain_internvl.py, pretrain_deepseekvl.py, pretrain_whisper.py, pretrain_lumina.py — dedicated…
- FSDP2-based entry: pretrain_transformers.py or mindspeed_mm/fsdp/train/trainer.py or mindspeed_mm/fsdp/tasks//train.py — newer models…
What it can do on your machine
Read from SKILL.md and the folder at commit 62a4ecb. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
Shell commands in SKILL.md call:
pythonpip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
gitcode.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Mindspeed Mm Pipeline loads about 3.5k tokens when it runs, and up to ~9.2k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 1,050 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.
Safety
Auto-check passed
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); files beside SKILL.md are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 1,050 words (~3,497 tokens).
“This Skill is the routing entry point for all MindSpeed-MM Skills. It determines the model type based on user intent, routes to the corresponding Skill, and provides a complete pipeline overview.”
- name
- mindspeed-mm-pipeline
- keywords
- mindspeed-mm, router, model-index, skill-selection, overview
Files
SKILL.md and 2 other files (references) in skills/training/mindspeed-mm/mindspeed-mm-pipeline of ascend-ai-coding/awesome-ascend-skills.
- SKILL.md
- references/common-args.md
- references/model-registry.md
Open the folder on GitHubat commit 62a4ecb
Compare with similar skills
Mindspeed Mm Pipeline 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 |
|---|---|---|---|---|---|---|
| Mindspeed Mm Pipeline this skillascend-ai-coding/awesome-ascend-skills | 174 | — | ~3.5k | Automated safety check: Pass | None | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.9k | 14 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
Similar skills
Add Uint Support
pytorch/pytorch
Add unsigned integer (uint) type support to PyTorch operators by updating ATDISPATCH macros.
LLM Benchmarking with lm-evaluation-harness
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
Segment Anything Model Guide
Orchestra-Research/AI-Research-SKILLs
Guide to using Meta's Segment Anything Model for zero-shot image segmentation with point, box or mask prompts, or automatic mask generation.
1password
trpc-group/trpc-agent-go
Set up and use 1Password CLI (op). An agent skill from trpc-group/trpc-agent-go.
Planning With Files
jarrodwatts/claude-code-config
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.
More from ascend-ai-coding/awesome-ascend-skills
All 70 skills in this repoAscend Dmi
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…
Ascendc
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.
Atc Model Converter
ascend-ai-coding/awesome-ascend-skills
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation.
External Cannbot Ops Pypto Op Develop
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。
External Gitcode Ascend Megatron Change Analyzer
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.
External Gitcode Ascend Megatron Commit Tracker
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.
Related
Categories
Questions about Mindspeed Mm Pipeline
What does Mindspeed Mm Pipeline do?
MindSpeed-MM skill router and model index for Huawei Ascend NPU. Mindspeed Mm Pipeline is an agent skill from ascend-ai-coding/awesome-ascend-skills. MindSpeed-MM skill router and model index for Huawei Ascend NPU.
When should I use Mindspeed Mm Pipeline?
Mindspeed Mm Pipeline fits situations like: the user is uncertain which MindSpeed-MM skill to use; needs to choose between understanding/generative/omni/audio model categories; wants an overview of the full training pipeline.
How do I install Mindspeed Mm Pipeline in Claude Code?
Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill mindspeed-mm-pipeline -a claude-code`. Or copy the skill folder (skills/training/mindspeed-mm/mindspeed-mm-pipeline in ascend-ai-coding/awesome-ascend-skills) into .claude/skills/mindspeed-mm-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Mindspeed Mm Pipeline in Codex?
Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill mindspeed-mm-pipeline -a codex`. Or copy the skill folder (skills/training/mindspeed-mm/mindspeed-mm-pipeline in ascend-ai-coding/awesome-ascend-skills) into .agents/skills/mindspeed-mm-pipeline in your project. Codex loads it when a task matches its description.
Can I use Mindspeed Mm Pipeline in Cursor, Gemini CLI or GitHub Copilot?
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 mindspeed-mm-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mindspeed-mm-pipeline, .gemini/skills/mindspeed-mm-pipeline, .github/skills/mindspeed-mm-pipeline and .opencode/skills/mindspeed-mm-pipeline in your project.
What does Mindspeed Mm Pipeline need to run?
Going by SKILL.md and its folder, Mindspeed Mm Pipeline needs the command-line tools its instructions call (python and pip). Our summary lists: Python 3; Docker.
Does Mindspeed Mm Pipeline access the network?
SKILL.md names 1 domain. As links in the text: gitcode.com. This is read from the text; nothing was executed.
Is Mindspeed Mm Pipeline safe to install?
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. Review the folder before installing.
What licence does Mindspeed Mm Pipeline use?
No licence was found for Mindspeed Mm Pipeline or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Mindspeed Mm Pipeline use?
About 3.5k tokens (SKILL.md is roughly 14k 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 5.7k tokens, read only when the agent opens those files.
What are the alternatives to Mindspeed Mm Pipeline?
Skills that share tags, products or a category with Mindspeed Mm Pipeline: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mindspeed Mm Pipeline?
ascend-ai-coding (a GitHub organization) maintains it in ascend-ai-coding/awesome-ascend-skills, which has 174 GitHub stars. The repository holds 70 skills in this directory. The repository was last updated on October 9, 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.