BC Amazon Listing Auditor for Chinese Sellers
专为中国跨境卖家设计的亚马逊Listing诊断工具，自动检测翻译错误、文化偏差、措辞问题和关键词缺失，帮助提升欧美买家转化率。Amazon listing audit skill for Chinese cross-border sellers — flags translation errors, cultural misfires, keyword gaps, and awkward phrasing that kills conversions with Western buyers. Triggers: amazon listing audit, listing review, chinese seller amazon, listing quality, listing copy review, 亚马逊listing审核, listing诊断, 跨境电商listing, listing翻译检查
As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 60/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (Amazon Listing Auditor for Chinese Sellers) differs from the folder (cn-amazon-listing-auditor)
- 55Failures and branches. 1 branches
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 20 steps
- 100Execution cost. Instruction body is 978 tokens
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)
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 407: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 20 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.