BF alibabacloud-remote-skills-connector
Use when a user asks what the Alibaba Cloud Remote Skills Connector can do, which hosted Alibaba Cloud skills are currently available, or requests Alibaba Cloud capability onboarding; wants to inspect, query, diagnose, audit, create, deploy, configure, update, resize, restart, repair, restore, or delete Alibaba Cloud (阿里云/Aliyun) resources; uses Chinese triggers such as 查询, 诊断, 巡检, 创建, 删除, 更新, 升配, 扩缩容, 重启, and 修复; continues an existing AgentHub task; or troubleshoots this connector's discovery/authentication—even without a product name. Exclude other clouds, general knowledge/architecture/pricing questions, and requests for local CLI/SDK/OpenAPI/Terraform/ROS execution or code.
Use when a user asks what the Alibaba Cloud Remote Skills Connector can do, which hosted Alibaba Cloud skills are currently available, or requests Alibaba…
As a process F 60/100 · Will not run — References files that are not bundled: scripts/agenthub.py
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5668 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: scripts/agenthub.py
Process rating: all ten parameters 60/100
- 0Tools and files. 1 referenced file(s) missing: scripts/agenthub.py
- 0Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 5668 tokens
- 100Steps. 31 steps
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- +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
- +1No license
- +2Single-language instructions
- +3Description length 686: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (14 code blocks)
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.