AC amazon-review-reveyes
使用 Reveyes API 批量抓取亚马逊商品评论，支持 20 个站点。 输出完整评论数据（含所有字段），并由 AI 从跨境电商运营者视角深度分析差评， 提供产品质量、物流包装、Listing 准确性、客服反馈、改善优先级等结构化分析报告。 Use when: 用户提到抓评论、查差评、分析竞品口碑、给出 ASIN 编号需要评论数据或运营分析。 NOT for: 分析已经抓好的本地评论文件，或查询亚马逊商品价格/销量。
As a process C 53/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency
How to improve
For the model run — optional
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "requires"
Process rating: all ten parameters 53/100
- 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
- 40Consistency. Frontmatter name (amazon-review-reveyes) differs from the folder (reveyes-skill)
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 61 steps
- 100Execution cost. Instruction body is 1600 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 211: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 61 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.
External checks
ClawHub: clean
This skill appears to be a purpose-aligned Amazon review API helper, but users should understand that their product and review queries go to an external provider and outputs may include public reviewer identifiers.
LLM: benign (medium) · VirusTotal: · 29 May 2026