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BB huawei-cloud-swr-image-automation

Huawei Cloud SWR (Software Repository for Container) image automation and operations skill using hcloud CLI. Use this skill when the user wants to: (1) configure cross-region image sync (auto or manual), (2) manage SWR triggers for auto-deploy to CCE/CCI, (3) query available sync target regions, (4) check sync job status, (5) create/update/delete trigger configurations. Trigger: user mentions "SWR automation", "SWR 自动化", "镜像同步", "SWR sync", "跨区域同步", "cross-region sync", "触发器", "SWR trigger", "自动部署", "auto deploy", "镜像复制", "image replication", "SWR 触发器"

ClawHub Agent Skills author: huaweiclouddev-dev v1.0.0 MIT-0 10 files body ≈ 5 789 tokens Open the sourceclawhub.ai↗ analyzed 32 h ago

Huawei Cloud SWR (Software Repository for Container) image automation and operations skill using hcloud CLI.

As a process B 79/100 · Nearly there — weak spots: progress reporting

IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
81/100
safety, quality, tests
Safety 60%
80
Quality 40%
83
Run on models
none yet
Process rating
B
79/100
Nearly there
Progress reporting w 2
0
Failures and branches w 10
55
Tools and files w 18
60
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: huawei-cloud-swr-image-automation (ClawHub)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:49
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:54
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:71
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:76
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5789 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "id"

Process rating: all ten parameters 79/100

  • 0Progress reporting. Says nothing while it works
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5789 tokens
  • 85Steps. 77 steps, 1 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (3 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 8 example trigger phrases
  • +3Description length 558: enough signal without eating the budget
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 77 items
  • +3Output format is stated explicitly
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (8 of 8)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.

External checks

ClawHub: suspicious
This skill is purpose-aligned, but it needs Review because its guides include high-impact cloud deployment changes and remote CLI installation steps without enough local warnings or integrity checks.
LLM: suspicious (medium) · 3 Aug 2026