huawei-cloud-install-openjiuwenswarm

huawei-cloud-install-openjiuwenswarm is a skill for Claude Code, Codex from huaweicloud/huaweicloud-skills. It costs 364 tokens per session (4,377 once invoked), scanned A, original, MIT.

A local installer and startup tool for JiuwenSwarm, an AI agent system, inside a Huawei Cloud development container. It downloads, configures, and starts the service using local credentials.

In plain words
What is it for?
It is for first-time JiuwenSwarm deployment, starting the service locally, configuring Huawei Cloud access, and selecting an available model.
Why use it?
It removes the need to perform the installation and setup steps manually, and can retry important steps when they fail.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for first-time JiuwenSwarm deployment, starting the service locally, configuring Huawei Cloud access, and selecting an available model.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add huaweicloud/huaweicloud-skills --skill huawei-cloud-install-openjiuwenswarm
Clone the repo
git clone --depth 1 https://github.com/huaweicloud/huaweicloud-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for huawei-cloud-install-openjiuwenswarm

README.md
[![agentmods](https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm/github.svg)](https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm)
Your own site
<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for huawei-cloud-install-openjiuwenswarm

Your own site · 80×15
<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-install-openjiuwenswarm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 364 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,377 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 5 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 36
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 264
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 268
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 270
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium Excessive Agency · line 186
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00364 $0.04377
Opus 5 $0.00182 $0.02188
Sonnet 5 $0.00073 $0.00875
Haiku 4.5 $0.00036 $0.00438

Measured yesterday against content hash aa2e0596d78f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

huawei-cloud-install-openjiuwenswarm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/01_download.py, scripts/02_extract.py, scripts/03_configure.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/devtools/openjiuwen/huawei-cloud-install-openjiuwenswarm/SKILL.md · 416 lines

How it starts

The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Local JiuwenSwarm Installation

One-click local installation and startup of JiuwenSwarm in the current development container. Reads credentials from local configuration (settings.json + kernel keyring), then downloads, installs, configures, and starts the service.


Overview

Function Positioning

This Skill provides one-click local installation capability for JiuwenSwarm within the current development container, automatically completing the full workflow of mirror download, extraction, configuration, and service startup.

Core Capabilities

  • Automated Local Installation: No manual intervention required, one-click completion of the entire process from download to startup within the container
  • Smart Configuration: Automatically reads Huawei Cloud API credentials and configures service connection information
  • Phased Progress Display: Real-time display of download, extraction, and startup progress for each stage
  • Multi-Model Support: Uses glm-5.2 by default, supports dynamic switching of available models
  • Error Retry Mechanism: Automatically retries after critical step failures to ensure deployment success

Use Cases

  • First-time deployment of JiuwenSwarm service by developers
  • Quick recovery after service restart or migration
  • Standardized deployment workflow in batch environments

Security Features

  • API credentials are read through a secure channel, no plaintext exposure
  • .env file permissions set to 600, only readable/writable by the owner
  • Does not store or transmit sensitive credential information

Mandatory Invocation Rules

  1. CRITICAL — Invoke this Skill first, no exceptions: When a user makes a request like "部署JiuwenSwarm/deploy JiuwenSwarm", "安装JiuwenSwarm/install JiuwenSwarm", "启动JiuwenSwarm/start JiuwenSwarm", "部署workswarm/deploy workswarm", "安装WorkSwarm/install WorkSwarm", "启动workswarm/start workswarm", the agent MUST immediately stop whatever it is doing and run the 5 phase scripts in strict sequential order (01_download → 02_extract → 03_configure → 04_start → 05_url). Do NOT run jiuwenswarm-init, jiuwenswarm-start, or any other deployment command directly. Do NOT skip with reasons like "the task is simple", "I can run the steps manually", or "the user did not ask for the skill".

Read the full file on GitHub · 416 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday Changed · +2 lines · +134 tokens per session aa2e0596d78f
  2. 9d ago First seen · 414 lines · 230 tokens per session scan A 7196899c7d50

Subscribe to this mod's changes

huawei-cloud-install-openjiuwenswarm is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (49 stars, last pushed yesterday), licensed MIT. It adds 364 tokens to every session and 4,377 once invoked, about $0.0018 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

deploy-docker-compose

Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…

omnigent-ai/omnigent · 84 tokens

compute-env-setup

Set up a reproducible Feynman compute environment for research jobs. Use when a task needs Python/R packages, GPU libraries, containers, Modal, SSH, caches, or managed model runtime setup.

companion-inc/feynman · 45 tokens

securing-kubernetes-on-cloud

This skill covers hardening managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring. It addresses cloud-specific security features including IRSA for EKS, Workload Identity for…

xalgorix/xalgorix · 80 tokens

detecting-privilege-escalation-in-kubernetes-pods

Detect and prevent privilege escalation in Kubernetes pods by monitoring security contexts, capabilities, and syscall patterns with Falco and OPA policies.

xalgorix/xalgorix · 40 tokens

implementing-rbac-hardening-for-kubernetes

Harden Kubernetes Role-Based Access Control by implementing least-privilege policies, auditing role bindings, eliminating cluster-admin sprawl, and integrating external identity providers.

xalgorix/xalgorix · 41 tokens

docker-socket-mount

Docker / containerd socket mounted into a container → host RCE. Common in CI runners, GitOps controllers (ArgoCD, Flux), and 'Docker-in-Docker' setups. Single-command escape via docker run --rm --privileged -v /:/host alpine chroot /host.

PurpleAILAB/Decepticon · 67 tokens