Keyword Competition Analysis

Community

kennyzir

keyword-competition-analysis

谷歌关键词竞争度分析。当用户要求分析某个关键词的搜索竞争度、SEO难度、关键词排名机会、市场调研，或要求"分析下XXX关键词"时触发。使用浏览器抓取Google搜索结果页作为主要数据源，输出结构化竞争度报告。

Overview

Publisher	kennyzir
Repository	`7deer_skills`
Skill name	`keyword-competition-analysis`
Stars	329
Forks	143
Bundled files	1
License	MIT
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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by kennyzir on GitHub. Read the source before you install it.

Installation

Install the Keyword Competition Analysis 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/kennyzir/7deer_skills/tree/main/keyword-competition-analysis
Enable the skill in any chat where you want it available.

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/kennyzir/7deer_skills.git /tmp/7deer_skills
mkdir -p .claude/skills
cp -r /tmp/7deer_skills/keyword-competition-analysis .claude/skills/keyword-competition-analysis

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

Use it in TypingMind

Enable Keyword Competition Analysis 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 Keyword Competition Analysis 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 Keyword Competition Analysis 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.

Keyword Competition Analysis

基于 Google 搜索结果页的关键词竞争度分析技能。

工作流程

Step 1：发起搜索

使用 browser 工具打开 Google 搜索结果页：


https://www.google.com/search?q=<URL编码的关键词>

Step 2：获取快照

用 browser snapshot compact=true 抓取搜索结果页，识别：

广告数量和广告主
前10自然结果标题 + 域名
是否有精选摘要、视频结果、People Also Search For
结果类型分布（官方文档/社区/工具/视频/论坛）

Step 3：二次验证（如需要）

打开1-2个典型结果页面，快速确认：

内容深度（页面字数/内容量级）
页面优化痕迹（标题、H标签、keywords标签）
域名大致权重感

Step 4：输出报告

按以下结构输出，详见 references/output-template.md：

基本信号评分表
竞争者画像
机会识别
综合判断

评分维度说明

维度	评估重点
广告主密度	多 = 商业价值高 = 竞争激烈
结果主体	高权重站（官方/维基/Quora）为主 = 壁垒高
内容深度	300字浅页面 vs 3000字+深度内容
精选摘要	有 = SEO空间被压缩
视频结果	有 = 视频布局已是红海
域名年龄感	全是老站 = 难；有机会站点出现 = 可切入

低竞争突破口识别

结果里有 PDF/PPT/论坛/Quora → 内容生态弱，机会
没有视频结果 → 视频是机会
工具/导航类结果多 → 内容站有机会
Search Intent 混杂（教程+产品混排）→ 细分人群可切

长尾词发现

从 People Also Search For 区域提取高价值长尾方向：

资源导向（...GitHub, ...examples）
评测导向（Best ...，...vs...）
教程导向（how to ..., ...tutorial）

注意事项

Google 搜索有反爬，优先用 browser 工具而非 web_search
不要依赖结果总数（谷歌已取消精确数字）
综合判断要带时效性提示（新市场窗口 vs 成熟红海）

Bundled files

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

references/output-template.md1 KB

Frequently asked questions

What does the Keyword Competition Analysis AI skill do?

Why use Keyword Competition Analysis on TypingMind?

Because you install it once and use it with any model. Keyword Competition Analysis 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 Keyword Competition Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kennyzir/7deer_skills/tree/main/keyword-competition-analysis. 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 Keyword Competition Analysis?

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 Keyword Competition Analysis?

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

Is the Keyword Competition Analysis AI skill free?

Yes. It is published on GitHub by kennyzir under the MIT license. 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

Openclaw Docker E2e Authoring

openclaw

OrganizationPopular

Author OpenClaw Docker E2E and live provider Docker lanes.

Openclaw Parallels Smoke

openclaw

OrganizationPopular

Prepare, snapshot, run, rerun, debug, or interpret OpenClaw Parallels guest install, onboarding, gateway smoke, and upgrade checks across macOS, Windows, and Linux.

Openclaw Update

Route routine updates of an existing local or remote OpenClaw Gateway to its installation owner, with automatic session recovery. Defer to deployment-specific skills when available.

Tag Duplicate Prs Issues

openclaw

OrganizationPopular

Use gitcrawl to search duplicate OpenClaw PRs/issues, group related work in prtags, and sync duplicate state to GitHub.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Keyword Competition Analysis

工作流程

Step 1：发起搜索

Step 2：获取快照

Step 3：二次验证（如需要）

Step 4：输出报告

评分维度说明

低竞争突破口识别

长尾词发现

注意事项

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now