BA 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 A 83/100 · Runs to the end — weak spots: progress reporting
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 · 0
✓ No critical or high findings
Files scanned: 17. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6067 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "updated" - note
frontmatter-keyunknown frontmatter key "owner"
Process rating: all ten parameters 83/100
- 0Progress reporting. Says nothing while it works
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 6067 tokens
- 85Steps. 40 steps, 3 vague phrases
- 100Result and completion. Output format and completion criterion are stated
- 100When it triggers. States when to use and when not to
- 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
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 18 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
- +4Description does not say when NOT to use the skill (false activations)
- -254 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +3Description length 677: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 40 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +4Reference files are cited in the instructions (14 of 14)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.