AC promo-traffic-stress-monitor
Monitor traffic efficiency and conversion load during major promos (Black Friday, Cyber Monday, Christmas peaks, flash sales) and advise dynamic ad spend, restock, and traffic allocation. Use in the first ~4 hours after a promo goes live, when ROI drops below breakeven during a sale, when hero SKUs sell out instantly, when the user mentions scaling or cutting ads mid-campaign, server or checkout strain, or "traffic is huge but orders aren't." Steps implied: real-time (or latest) traffic → conversion efficiency → if strong, recommend scaling spend or shifting budget to winners; if weak, recommend landing-page and funnel checks before spend. Also trigger on stockouts under load, CAC spike during promos, or reallocating budget between campaigns. Do NOT use for evergreen SEO-only plans with no live promo window, or pure creative briefs without performance or inventory context.
As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Monitor traffic efficiency and conversion load during major promos… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 19 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 839 tokens
- medium 3 test cases, all positive: not one "should refuse" or "should ask first"
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
- +3Description length 885: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +4Structure: 11 headings
- +3Step-by-step instructions: 19 items
- +4Reference files are cited in the instructions (1 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.