AB huawei-cloud-cloudrobo-resource
Query CloudRobo resource quotas and resource pools — list workspace-level and Domain-level quotas with CCE/ModelArts isolation (CCE: cpu/memory/gpu, ModelArts: npu), list resource pools with multi-condition filtering (type/sub-type/pool-type/usages), and show resource pool details with node-level information (name, status, resources, labels). Provides compute capacity visibility for training, evaluation, and inference workloads. Triggers include: resource quota query, resource pool query, resource pool list, resource pool detail, quota list, Domain quota aggregation, CCE quota, ModelArts quota, 资源配额查询, 资源池查询, 资源池列表, 资源池详情, 配额查询.
Query CloudRobo resource quotas and resource pools — list workspace-level and Domain-level quotas with CCE/ModelArts isolation (CCE: cpu/memory/gpu…
As a process B 70/100 · Nearly there — weak spots: when it triggers, running it twice, progress reporting
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 70/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 33 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1948 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)
- +1No license
- +2Single-language instructions
- +3Description length 636: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 33 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (7 of 7)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.