AB huawei-cloud-cc-gcb-query
Queries Huawei Cloud Cloud Connect (CC) Global Connection Bandwidth (GCB) resources via hcloud CLI. Covers single GCB detail query (including bound instance info), GCB list query with filters, GCB tenant configuration query (size ranges, quotas, charge modes, supported services), and list of GCBs eligible for binding to a specific service type. No write operations. Use this skill when the user needs to inspect global connection bandwidth details, check GCB-bound instances, review GCB tenant configs and quotas, or find GCBs available for binding. Triggers include: 全域互联带宽, GCB, Global Connection Bandwidth, global-connection-bandwidth, 云连接带宽, CC带宽, bandwidth config, 绑定带宽, support binding bandwidth, gcb-query.
Queries Huawei Cloud Cloud Connect (CC) Global Connection Bandwidth (GCB) resources via hcloud CLI.
As a process B 71/100 · Nearly there — weak spots: result and completion, failures and branches, running it twice
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 · 0
✓ No critical or high findings
Files scanned: 10. 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 71/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 15 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 10 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2415 tokens
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -31 of 1 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 715: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 10 items
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.