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BB huawei-cloud-dws-mem-diag

DWS cluster memory high root cause diagnosis skill, based on KooCLI v3.2.0+ and DWS Autopilot MCP Server. Automatically collects memory metrics, analyzes root causes (customer-side / system-side), and outputs a standardized diagnosis report. Applicable to DWS cluster memory usage too high, memory alarms, OOM scenarios. Trigger words: "内存高", "内存告警", "内存诊断", "内存使用率过高", "内存不足", "OOM", "内存溢出", "动态内存使用率超阈值", "high memory", "memory alarm", "memory diagnosis"

ClawHub Agent Skills author: huaweiclouddev-dev v1.0.1 MIT-0 8 files body ≈ 6 466 tokens Open the sourceclawhub.ai↗ analyzed 33 h ago

DWS cluster memory high root cause diagnosis skill, based on KooCLI v3.2.0+ and DWS Autopilot MCP Server. Automatically collects memory metrics, analyzes root…

As a process B 71/100 · Nearly there — weak spots: consistency, running it twice, progress reporting

AnalyzerAI and agentsData and analyticstype 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
84/100
safety, quality, tests
Safety 60%
85
Quality 40%
83
Run on models
none yet
Process rating
B
71/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Consistency w 8
40
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-dws-mem-diag (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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:27
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:36
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/
  • medium Dangerous commands cmd-privilege references/cli-installation-guide.md:45
    Privilege escalation / world-writable permissions
    sudo mv hcloud /usr/local/bin/

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6466 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "trigger"
  • note frontmatter-key unknown frontmatter key "input_schema"
  • note frontmatter-key unknown frontmatter key "output_schema"

Process rating: all ten parameters 71/100

  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 3 mutating operations with no state check
  • 40Consistency. Frontmatter name (huawei-cloud-dws-mem-diag) differs from the folder (huawei-cloud-dws-dymem-diag)
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 6466 tokens
  • 85Steps. 74 steps, 2 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Failures and branches. 2 branches, has a failure section
  • low 10 top-level sections: this looks like several domains in one skill

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)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 456: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 74 items
  • +3Output format is stated explicitly
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

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

External checks

ClawHub: suspicious
The skill is a coherent read-only DWS diagnosis helper, but it persists potentially sensitive reports locally and includes unsafe cloud-secret setup examples that need review before installation.
LLM: suspicious (high) · 4 Aug 2026