AC aliyun-global-search
Query Alibaba Cloud product information, documentation, parameters, features, and pricing from official sources without login. Use when the user asks about Alibaba Cloud products (ECS, RDS, OSS, SLB, etc.), needs product documentation, wants to compare product specifications, or needs help finding specific product parameters and features.
As a process C 59/100 · Has gaps — weak spots: failures and branches, consistency, execution cost
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securitySKILL.md:253Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| 渗透测试服务 | Penetration Testing | 挖掘业务流程中的安全缺陷 |
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 9232 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 59/100
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 9 mutating operations with no state check
- 40Consistency. Frontmatter name (aliyun-global-search) differs from the folder (alibabacloud-global-search)
- 40Execution cost. Instruction body is 9232 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 136 steps
- 100Progress reporting. Reports progress
- low 11 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
- +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 340: enough signal without eating the budget
- +4Structure: 117 headings
- +3Step-by-step instructions: 136 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.