AB huawei-cloud-cdn-traffic-anomaly-analysis
Analyze CDN domain traffic anomalies using hcloud CLI. Query billing mode and traffic/bandwidth metrics for specified domains, compare against 3-month baseline and absolute thresholds to identify traffic theft or abuse. Use this skill when the user wants to: (1) analyze CDN domain traffic anomalies, (2) check if a domain has traffic theft or abuse, (3) query CDN billing mode and traffic/bandwidth metrics, (4) compare current traffic against historical baseline. Triggers include: CDN流量异常, 流量异常分析, 域名流量分析, 流量盗刷, 带宽异常, 95带宽异常, 流量突增, 流量对比, 基准分析, traffic anomaly, bandwidth anomaly, CDN traffic analysis, traffic theft detection, baseline comparison
Analyze CDN domain traffic anomalies using hcloud CLI.
As a process B 77/100 · Nearly there — weak spots: progress reporting
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: 16. 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 77/100
- 0Progress reporting. Says nothing while it works
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, web, 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. 31 steps, 1 vague phrases
- 100Result and completion. Output format and completion criterion are stated
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3641 tokens
- 100Running it twice. Mutating operations check current state
- low 12 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)
- -226 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 649: enough signal without eating the budget
- +4Structure: 21 headings
- +3Step-by-step instructions: 31 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (13 of 13)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.