BB huawei-cloud-sfsturbo-list
Query the list of Huawei Cloud SFS (Scalable File Service, 弹性文件服务 / SFS Turbo) file systems under the current tenant / project, focused on the SFS NAME list. Returns each file system's name, id, status, size, protocol and region; can also output a pure SFS name-only list. Supports pagination (limit/offset). Uses the KooCLI command `hcloud SFSTurbo ListShares --cli-region={region}` (primary) against the v1 API, or the huaweicloudsdksfsturbo Python SDK (fallback). Read-only — never creates, modifies or deletes any file system. Use this skill whenever the user wants to list/inspect the SFS file systems of the tenant or query the SFS name list, e.g. for storage inventory, daily inspection, or cost review. Triggers include: "list SFS", "SFS list", "query SFS names", "SFS name list", "弹性文件服务列表", "查询SFS", "SFS名称", "sfs 列表", "list shares", "list file systems", "how many SFS", "SFS Turbo 列表".
Query the list of Huawei Cloud SFS (Scalable File Service, 弹性文件服务 / SFS Turbo) file systems under the current tenant / project, focused on the SFS NAME list.
As a process B 70/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
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.
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
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:12Privilege escalation / world-writable permissionssudo mv hcloud /usr/local/bin/
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medium Dangerous commands
cmd-privilegereferences/cli-installation-guide.md:18Privilege escalation / world-writable permissionssudo mv hcloud /usr/local/bin/
Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 70/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 23 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1636 tokens
- low The response is described with custom markup (10 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)
- +3Description length 896: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -31 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +4Structure: 13 headings
- +3Step-by-step instructions: 23 items
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.