AD amazon-selection-agent
Amazon 产品选品 Agent，面向有经验的亚马逊卖家的全链路选品工具。 覆盖四大模块：市场扫描（BSR分布/价格带/季节性/集中度）→ 竞品拆解（Top20画像/评论痛点/差异化机会） → FBA利润测算（费用/广告/头程/ROI）→ 关键词挖掘（搜索量/长尾词/PPC参考）。 支持双模式：模式A「品类探索」——卖家无明确目标，扫描品类大盘推荐细分赛道； 模式B「产品深挖」——卖家提供 ASIN/关键词/链接，深度分析+利润测算+决策建议。 触发场景：亚马逊选品、Amazon product research、FBA利润计算、竞品分析、 关键词机会、类目分析、"帮我看看这个品类"、"分析这个产品"、"这个能不能做"、 "算一下利润"、"这个词怎么样"、"find products to sell on Amazon"。
Amazon 产品选品 Agent，面向有经验的亚马逊卖家的全链路选品工具。 覆盖四大模块：市场扫描（BSR分布/价格带/季节性/集中度）→ 竞品拆解（Top20画像/评论痛点/差异化机会） → FBA利润测算（费用/广告/头程/ROI）→ 关键词挖掘（搜索量/长尾词/PPC参考）。…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 46/100
- 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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 57 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1936 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 367: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 57 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.