Amazon Keyword Research

Community

liangdabiao

amazon-keyword-research

亚马逊卖家关键词研究和市场机会分析。获取自动完成建议（长尾关键词），分析竞争格局，并评估12个亚马逊市场（美国/英国/德国/法国/意大利/西班牙/日本/加拿大/澳大利亚/印度/墨西哥/巴西）的任何关键词的市场机会。无需API密钥。当用户提到亚马逊产品研究、寻找在亚马逊上销售的产品、亚马逊关键词创意、利基分析、亚马逊竞争分析、亚马逊市场机会、比较亚马逊关键词、评估产品是否值得销售、亚马逊自动完成数据、亚马逊产品的季节性需求，或任何与研究在亚马逊上销售什么相关的内容时，确保使用此技能 — 即使他们没有明确说'关键词研究'。当用户问模糊问题时也触发，如'这是一个好的销售产品吗？'、'X在亚马逊上的竞争如何？'、'我应该卖X还是Y？'，或'人们在亚马逊上搜索什么？'。

Overview

Publisher	liangdabiao
Repository	`Amazon-Skills-Liang`
Skill name	`amazon-keyword-research`
Stars	99
Forks	20
Bundled files	3
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by liangdabiao on GitHub. Read the source before you install it.

Installation

Install the Amazon Keyword Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/liangdabiao/Amazon-Skills-Liang/tree/main/skills/amazon-keyword-research
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/liangdabiao/Amazon-Skills-Liang/tree/main/skills/amazon-keyword-research

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/liangdabiao/Amazon-Skills-Liang.git /tmp/Amazon-Skills-Liang
mkdir -p .claude/skills
cp -r /tmp/Amazon-Skills-Liang/skills/amazon-keyword-research .claude/skills/amazon-keyword-research

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amazon Keyword Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Amazon Keyword Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Amazon Keyword Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

亚马逊关键词研究 🔍

亚马逊卖家免费关键词研究工具。无需API密钥 — 开箱即用。

功能

长尾关键词挖掘：从亚马逊自动完成引擎提取100-200个真实搜索词
竞争格局分析：产品数量、价格范围、平均评分、评论分布、顶级品牌
季节性趋势检测：12个月谷歌趋势数据，识别旺季和需求变化
市场机会评分：1-10分，结合竞争密度、价格空间和需求信号
多市场支持：美国、英国、德国、法国、意大利、西班牙、日本、加拿大、澳大利亚、印度、墨西哥、巴西
关键词比较：多个关键词的并排分析

使用示例

用户可以自然提问。例如：


研究亚马逊美国的关键词"portable blender"


为"yoga mat"查找亚马逊长尾关键词


我想卖阻力带。亚马逊关键词格局如何？


比较亚马逊美国的"laptop stand"和"monitor stand" — 哪个机会更大？


分析亚马逊德国的"Küchenmesser"


研究亚马逊美国、英国和德国的"water bottle"

工作流程

第一步：收集自动完成数据

运行捆绑脚本收集亚马逊自动完成建议：

bash
<skill>/scripts/research.sh "<关键词>" [市场]

参数：

关键词（必填）：要研究的种子关键词
市场（可选）：us（默认）、uk、de、fr、it、es、jp、ca、au、in、mx、br

脚本功能：

使用种子关键词查询亚马逊自动完成API
使用前缀扩展："best [关键词]"、"cheap [关键词]"、"top [关键词]"
使用a-z后缀扩展："[关键词] a"、"[关键词] b"、... "[关键词] z"
返回去重、排序的真实搜索建议列表 — 每行一个

为什么重要： 亚马逊自动完成反映了真实购物者实际输入的内容。这些不是猜测 — 它们是来自亚马逊搜索引擎的直接需求信号。前缀和字母扩展捕获了基本自动完成遗漏的长尾词，这些词通常竞争较低且意图较高。

示例：

bash
<skill>/scripts/research.sh "portable blender" us
# 返回100-200个长尾关键词

对于多市场研究，请每个市场运行一次脚本。

第二步：分析竞争

使用 web_search 收集竞争对手情报：

搜索 "<关键词>" site:amazon.com — 记下约结果数量以了解竞争密度
搜索 "<关键词>" amazon best sellers price review — 提取价格模式、评分平均值、主导品牌
总结：总竞争对手数量、价格范围（最低/平均/最高）、平均星级、可见度最高的Top 5品牌

为什么重要： 没有竞争背景的原始关键词量毫无意义。一个有10,000次搜索但被3个拥有10,000+评论的老牌品牌主导的关键词，与具有相同搜索量但卖家分散的关键词相比，是完全不同的机会。价格范围揭示了利润潜力 — 如果所有产品都在10美元以下，FBA费用后将非常微薄。

第三步：检查季节性

在谷歌趋势上使用 web_fetch：


https://trends.google.com/trends/explore?q=<关键词>&geo=US

如果谷歌趋势返回429错误，回退到 web_search 获取季节性数据：


"<关键词>" seasonal trends demand peak months

识别：趋势方向（上升/下降/稳定）、季节性高峰（哪些月份）、同比变化。

为什么重要： 季节性决定了现金流风险。一个80%销量集中在第四季度的产品意味着你需要提前数月准备好库存资金，其余时间可能面临滞销库存。上升趋势意味着需求增长和新进入者的空间；下降趋势意味着你在争夺不断缩小的市场份额。这种背景将关键词从数字变成商业决策。

第四步：综合报告

将所有数据组合成下面的输出格式。

为什么结构重要： 按意图（商业意图vs信息意图vs利基意图）对关键词分组帮助卖家不仅了解人们搜索什么，还了解为什么搜索。机会评分将多个信号浓缩成一个可操作的数字，但其背后的细分才是真正为决策提供依据 — 所以始终展示推理过程。

输出格式

使用以下结构呈现最终报告：


## 关键词研究报告：[关键词]
**市场：** 亚马逊 [美国/英国/德国/...]
**日期：** [当前日期]

### 1. 长尾关键词（找到[数量]个）

**高商业意图：**
- [包含"buy"、"best"、"vs"、"for"等的关键词]
- ...

**信息性/研究性：**
- [包含"how to"、"what is"、"review"等的关键词]
- ...

**利基/特定：**
- [表明明确购买意图的长而具体的关键词]
- ...

### 2. 竞争格局

| 指标 | 值 |
|--------|-------|
| 估计竞争对手数 | [数量] |
| 价格范围 | $[最低] - $[最高] |
| 平均价格 | $[平均] |
| 平均评分 | [星级] |
| 顶级品牌 | [品牌1、品牌2、品牌3...] |

### 3. 季节性趋势

[描述12个月趋势：高峰、低谷、稳定期]
[注意与关键词相关的即将到来的高峰季节]

### 4. 市场机会评分：[X/10]

**评分细分：**
- 竞争密度：[低/中/高] — [原因]
- 价格空间：[低/中/高] — [原因]
- 需求趋势：[增长/稳定/下降] — [原因]
- 利基潜力：[低/中/高] — [原因]

**建议：** [1-2句可操作的建议]

多关键词比较

当用户要求比较两个或更多关键词时，分别对每个关键词运行完整工作流程（第一步至第四步），然后以并排比较表呈现结果。

示例用户输入：


比较亚马逊美国的"laptop stand"、"monitor stand"和"tablet stand" — 我应该卖哪个？

如何执行： 运行脚本3次：

bash
<skill>/scripts/research.sh "laptop stand" us
<skill>/scripts/research.sh "monitor stand" us
<skill>/scripts/research.sh "tablet stand" us

然后对每个关键词完成第二步和第三步，并输出比较表：

指标	laptop stand	monitor stand	tablet stand
长尾关键词数量	—	—	—
平均价格	—	—	—
顶级品牌主导度	—	—	—
趋势方向	—	—	—
机会评分	—	—	—

以建议结束，说明哪个关键词机会最大及其原因。

局限性

关键词数量基于自动完成返回，可能不完整
竞争数据来自网络搜索，估计值
趋势数据来自谷歌趋势，可能有延迟
建议仅供参考 — 做出商业决策前进行自己的研究

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Amazon Keyword Research AI skill do?

Why use Amazon Keyword Research on TypingMind?

Because you install it once and use it with any model. Amazon Keyword Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Amazon Keyword Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liangdabiao/Amazon-Skills-Liang/tree/main/skills/amazon-keyword-research. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Amazon Keyword Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Amazon Keyword Research?

As many as you like. As long as a model supports skills, you can use Amazon Keyword Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Amazon Keyword Research AI skill free?

It is published on GitHub by liangdabiao. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Wayfinder

mattpocock

CommunityPopular

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Creative Ideation

Generate ideas via named methods from creative practice.

Inference Sh Cli

Run 150+ AI apps (image, video, LLM) via inference.sh CLI.

Firecrawl Build Search

firecrawl

OrganizationPopular

Integrate Firecrawl `/search` into product code and agent workflows. Use when an app needs discovery before extraction, when the feature starts with a query instead of a URL, or when the system should…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

亚马逊关键词研究 🔍

功能

使用示例

工作流程

第一步：收集自动完成数据

第二步：分析竞争

第三步：检查季节性

第四步：综合报告

输出格式

多关键词比较

局限性

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now