HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters.

No licenceAuto-check: warningsTesting & QA

Install Hccl Test

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add ascend-ai-coding/awesome-ascend-skills --skill hccl-test -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ascend-ai-coding/awesome-ascend-skills hccl-test --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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/hccl-test .claude/skills/hccl-test && rm -rf skills-src

Use ~/.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/

Facts

Skill name
hccl-test
GitHub stars
174
Token cost
~2.2k tokens
SKILL.md length
472 words
Files
12 (incl. scripts, references)
Skills in repo
70
Repo updated
First seen
Licence
None found

At a glance

HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters.

  • Works in 9 steps: Pre-test Checklist(多机测试必需) → MPI Installation → Tool Compilation → …
  • Testing distributed communication bandwidth
  • SKILL.md covers Overview, Quick Reference, 1. Pre-test Checklist(多机测试必需) and 2. MPI Installation, plus 6 more sections
  • Runs Shell and Python scripts from its folder; calls make and ssh

What it does

Hccl Test is an agent skill from ascend-ai-coding/awesome-ascend-skills. HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters. Use for testing distributed communication bandwidth, verifying HCCL functionality, and benchmarking collective operations like AllReduce, AllGather. Covers MPI installation, multi-node pre-flight checks (SSH/CANN version/NPU health), and production testing workflows.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `references/common-issues.md`, `references/docker-notes.md` and `references/parameters.md`).

It sits in Testing & QA, covering Load testing. 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

  • Testing distributed communication bandwidth
  • Verifying HCCL functionality
  • Benchmarking collective operations like AllReduce

Example prompts

  • “/hccl-test”

Requirements

  • Python 3
  • A Bash shell
  • Docker

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Pre-test Checklist(多机测试必需)
  2. MPI Installation
  3. Tool Compilation
  4. Testing Scenarios
  5. Parameters
  6. Results
  7. Actual Test Results
  8. Common Issues
  9. Scripts

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

    Ships 6 files in scripts/ (Shell and Python), which the agent can run.

    Shell commands in SKILL.md call:

    • make
    • ssh

    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):

    • hiascend.com
    • mpich.org

    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

Hccl Test loads about 2.2k tokens when it runs, and up to ~9.2k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 472 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.2k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningMentions a credentials file (SSH keys, cloud or package-manager tokens)SKILL.md:81
    ssh-copy-id -i ~/.ssh/id_rsa.pub root@<node1_ip>
  • WarningMentions a credentials file (SSH keys, cloud or package-manager tokens)SKILL.md:82
    ssh-copy-id -i ~/.ssh/id_rsa.pub root@<node2_ip>

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.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 472 words (~2,196 tokens).

name
hccl-test
keywords
hccl, 性能测试, 集合通信, 打流, allreduce, allgather, 多机测试, 910B

Read the full SKILL.md on GitHub

Files

SKILL.md and 11 other files (scripts, references) in skills/training/hccl-test of ascend-ai-coding/awesome-ascend-skills.

  • SKILL.md
  • references/common-issues.md
  • references/docker-notes.md
  • references/parameters.md
  • references/pre-test-checklist.md
  • references/testing-scenarios.md
  • scripts/hostfile-template.txt
  • scripts/multi-node-test.sh
  • scripts/parse-hccl-result.py
  • scripts/pre-test-check.sh
  • scripts/quick-verify.sh
  • scripts/setup-hccl-env.sh

Open the folder on GitHubat commit 62a4ecb

Compare with similar skills

Hccl Test 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.

Hccl Test compared with similar skills
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Go Testingcxuu/golang-skills1701 repos~1.3kAutomated safety check: PassApache-2.0
Goalcraftgrp06/goalcraft102—~3.8kAutomated safety check: PassMIT
Thinking Partnermattnowdev/thinking-partner206—~4.4kAutomated safety check: PassMIT
Visionkunchenguid/vision329—~2.9kAutomated safety check: PassMIT

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Categories

Questions about Hccl Test

What does Hccl Test do?

HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters. Hccl Test is an agent skill from ascend-ai-coding/awesome-ascend-skills. HCCL (Huawei Collective Communication Library) performance testing for Ascend NPU clusters.

When should I use Hccl Test?

Hccl Test fits situations like: testing distributed communication bandwidth; verifying HCCL functionality; benchmarking collective operations like AllReduce.

How do I install Hccl Test in Claude Code?

Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill hccl-test -a claude-code`. Or copy the skill folder (skills/training/hccl-test in ascend-ai-coding/awesome-ascend-skills) into .claude/skills/hccl-test in your project. Claude Code loads it when a task matches its description.

How do I install Hccl Test in Codex?

Run `npx skills add ascend-ai-coding/awesome-ascend-skills --skill hccl-test -a codex`. Or copy the skill folder (skills/training/hccl-test in ascend-ai-coding/awesome-ascend-skills) into .agents/skills/hccl-test in your project. Codex loads it when a task matches its description.

Can I use Hccl Test 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 hccl-test -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hccl-test, .gemini/skills/hccl-test, .github/skills/hccl-test and .opencode/skills/hccl-test in your project.

What does Hccl Test need to run?

Going by SKILL.md and its folder, Hccl Test needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (make and ssh). Our summary lists: Python 3; A Bash shell; Docker.

Does Hccl Test access the network?

SKILL.md names 2 domains. As links in the text: hiascend.com and mpich.org. This is read from the text; nothing was executed.

Is Hccl Test safe to install?

Our automated static check of SKILL.md flagged 2 warning(s): mentions a credentials file (ssh keys, cloud or package-manager tokens). Read the flagged lines before installing; the check is not a guarantee either way. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Hccl Test use?

No licence was found for Hccl Test or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Hccl Test use?

About 2.2k tokens (SKILL.md is roughly 8.8k 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 7k tokens, read only when the agent opens those files.

What are the alternatives to Hccl Test?

Skills that share tags, products or a category with Hccl Test: Writing Livekit Scenarios (livekit-examples/agent-starter-python, 264 stars), Go Testing (cxuu/golang-skills, 170 stars), Goalcraft (grp06/goalcraft, 102 stars) and Thinking Partner (mattnowdev/thinking-partner, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hccl Test?

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 8, 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.