AD amazon-category-research
Amazon Category Research Skill for sellers. Automated ASIN analysis, competitor research, and market intelligence. Use when user mentions: 亚马逊, Amazon, 类目调研, 类目分析, 品类分析, category research, 竞品分析, 竞品调研, competitor analysis, ASIN分析, ASIN调研, ASIN research, 选品, 选品分析, product research, 市场调研, market research, 产品调研, 产品分析, 亚马逊运营, Amazon FBA, FBA卖家, 运营分析, 销量分析, sales analysis, BSR排名, Best Sellers, 畅销榜, 热销榜, 排名分析, 卖家精灵, SellerSprite, SIF, 流量词, 流量分析, 关键词调研, keyword research, 广告分析, ad analysis, 利润率, 利润分析, 新品, 新品调研, 跟卖, 品牌分析, brand analysis, 店铺分析, store analysis, 数据采集, 数据抓取, data scraping, listing分析, listing优化, 产品详情, 产品信息采集, 月销量, monthly sales, 上架时间, listing date, FBA费用, FBA fee, review分析, review analysis, 评论分析, 评分分析, 站外流量, off-site traffic, 视觉文案, 产品主图, A+页面, A+ content
Amazon Category Research Skill for sellers.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- 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: 23. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 769 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "requires_browser" - note
frontmatter-keyunknown frontmatter key "requires_plugins" - note
frontmatter-keyunknown frontmatter key "max_asins" - note
frontmatter-keyunknown frontmatter key "default_site"
Process rating: all ten parameters 49/100
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (amazon-category-research) differs from the folder (amz-cat-research)
- 100Tools and files. No external tools needed
- 100Steps. 41 steps
- 100Execution cost. Instruction body is 3035 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -31 of 12 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 768: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (13 code blocks)
- +4Reference files are cited in the instructions (4 of 5)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.