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Agent skill

Linkfox AI Mode Google Search

by linkfox-ai in linkfox-ai/linkfox-skills

基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI…

MITAuto-check passedResearch & Science

Install Linkfox AI Mode Google Search

skills CLI
$ npx skills add linkfox-ai/linkfox-skills --skill linkfox-ai-mode-google-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install linkfox-ai/linkfox-skills linkfox-ai-mode-google-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/linkfox-ai/linkfox-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/linkfox-ai-mode-google-search .claude/skills/linkfox-ai-mode-google-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linkfox-ai-mode-google-search
GitHub stars
107
Token cost
~2.4k tokens
SKILL.md length
1,111 words
Files
5 (incl. scripts, references)
Skills in repo
177
Repo updated
First seen
Licence
MIT

At a glance

基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI…

  • Works in 4 steps: The required keyword is sent to Google… → Single-round only: each call handles… → For follow-up questions: the agent must… → …
  • Tasks that involve AI search optimization
  • SKILL.md covers Core Concepts, Parameters, Response Fields and 调用方式, plus 6 more sections
  • Runs Python scripts from its folder; calls python; needs LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY

What it does

Linkfox AI Mode Google Search is an agent skill from linkfox-ai/linkfox-skills. 基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI Mode、谷歌AI概览、谷歌AI搜索、海外深度调研、长尾选品调研、消费者偏好分析、网页要点总结、Google AI search, AI Overview, AI Mode, deep research, consumer preference analysis 等场景时触发此技能。即使用户未明确提到"Google AI"，只要其需求是"用谷歌搜索 + AI 总结网页要点"，也应触发此技能。

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api.md`, `references/onboarding.md` and `scripts/google_ai_search.py`).

It sits in Research & Science, covering AI search optimization, Web search and Deep research. The licence is MIT.

When your agent uses it

  • Tasks that involve AI search optimization
  • Tasks that involve Web search
  • Tasks that involve Deep research

Example prompts

  • “Google AI”
  • “用谷歌搜索 + AI 总结网页要点”
  • “/linkfox-ai-mode-google-search”

Requirements

  • Python 3
  • A credential in LINKFOX_AGENT_API_KEY
  • A credential in LINKFOXAGENT_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. The required keyword is sent to Google as the query and the AI Overview for it is captured.
  2. Single-round only: each call handles exactly one question. There is no prompts parameter for follow-ups.
  3. For follow-up questions: the agent must summarize the previous AI Overview answer (key points, citations, relevant context) and…
  4. All answers are returned as a single Markdown document under stdout, with citations linked to the source pages.

What it can do on your machine

Read from SKILL.md and the folder at commit 38fef04. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • skill.linkfox.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LINKFOX_AGENT_API_KEY
    • LINKFOXAGENT_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Linkfox AI Mode Google Search loads about 2.4k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 1,111 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from linkfox-ai/linkfox-skills at commit 38fef04, republished under its MIT licence (© linkfox-ai). 1,111 words, ~2,357 tokens.

Download SKILL.mdSave it as .claude/skills/linkfox-ai-mode-google-search/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
linkfox-ai-mode-google-search
description
基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI Mode、谷歌AI概览、谷歌AI搜索、海外深度调研、长尾选品调研、消费者偏好分析、网页要点总结、Google AI search, AI Overview, AI Mode, deep research, consumer preference analysis 等场景时触发此技能。即使用户未明确提到"Google AI"，只要其需求是"用谷歌搜索 + AI 总结网页要点"，也应触发此技能。

This skill calls Google Search in AI Mode to get the AI Overview answer for a single keyword. Only one question per call is supported — there is no multi-turn follow-up within a single request. The response is unstructured Markdown — summarize it directly, do not route it to a data-analysis sandbox.

Core Concepts

The tool drives Google's AI Mode (the panel that appears at the top of Google search results and synthesizes an answer with citations):

  1. The required keyword is sent to Google as the query and the AI Overview for it is captured.
  2. Single-round only: each call handles exactly one question. There is no prompts parameter for follow-ups.
  3. For follow-up questions: the agent must summarize the previous AI Overview answer (key points, citations, relevant context) and concatenate it with the new question into a new keyword, then make a fresh API call.
  4. All answers are returned as a single Markdown document under stdout, with citations linked to the source pages.

resultsNum reports how many AI Overview blocks were rendered; 0 means the keyword did not trigger an AI Overview on Google for the requested locale.

Parameters

ParameterTypeRequiredDescription
keywordstringYesGoogle search keyword. Sent as the q= parameter to Google AI Mode. For follow-up questions, the agent should summarize the previous answer and concatenate with the new question into this field.

Response Fields

FieldTypeDescription
stdoutstringMarkdown document with the AI Overview for the keyword, plus inline citation links
sourceUrlstringThe Google AI Mode search URL that was actually requested
resultsNumintegerNumber of AI Overview blocks rendered (0 = keyword did not trigger AI Overview)
code / errcodestring / integer200 on success; non-200 indicates a business error
msg / errmsgstringok on success; otherwise an error description
costTimeintegerAPI latency in milliseconds
costTokenintegerTokens consumed (only billed on success)
taskIdstringUpstream task identifier for tracing
typestringRender hint, fixed value stdoutWorkbenches

调用方式

  • API 端点：POST /aiMode/googleSearch（完整参数/响应/错误码见 references/api.md）
  • Python 脚本：python scripts/google_ai_search.py '<JSON 参数>' [--inline]
  • 成本约束：本工具会消耗算力；同一会话同一参数组合默认只调用一次，脚本带 24h 本地缓存。失败/空结果不得自动换关键词、翻页或改邮编连续试探；需要继续检索时先向用户说明会产生额外消耗。

输出策略（脚本默认行为）：

  • 始终将完整响应写入 <cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-ai-mode-google-search-<timestamp>.json（<cwd> 为脚本执行时的工作目录，在 Claude Code 里即当前项目目录；<session> 取自环境变量 SESSION_ID，按用户任务自动聚合；禁止写入 /tmp，当前目录不可写则报错）
  • 响应体 ≤ 8 KB：落盘后把完整 JSON 打印到 stdout
  • 响应体 > 8 KB：落盘后 stdout 只输出摘要（顶层字段、常见计数如 total/costToken、最大列表字段的长度 + 前 3 条样本）
  • 加 --inline 强制全量打印到 stdout（同样落盘）

读数据建议：先看摘要判断是否足够；需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取，避免整份 JSON 进入上下文。

解决认证和算力问题

发生以下异常情况时，采用 references/onboarding.md 引导解决问题：

异常情况
  • 未配置API Key：环境变量未配置 LINKFOX_AGENT_API_KEY，也未配置 LINKFOXAGENT_API_KEY。
  • 响应401或402状态码
  • 响应提示算力或余额不足：消息含"算力余额不足/计费不足/余额不足/quota exceeded/insufficient balance/套餐到期/需充值/请充值"，或类似含义的内容。

How to Build Queries

Each call takes a single keyword. For follow-up questions, the agent must summarize the previous result and build a new query.

Tips
  1. Front-load context in keyword: include market/region cues when relevant ("open-ear bone-conduction headphones US 2026") — the AI Overview is sensitive to phrasing.
  2. Match the language to the target market: ask in English for US/UK/AU markets, Japanese for JP, German for DE, etc. — the AI Overview is biased toward the locale's language.
  3. Use natural-language questions: phrasing like "compare against" / "what are the unsolved pain points" elicits richer AI Overview output than single keywords.
  4. For follow-ups, summarize and re-ask: when the user wants to dig deeper, the agent should summarize key points from the previous AI Overview response and concatenate with the new question into a new keyword for a fresh call. Example: "Based on the AI overview that top bone-conduction headphones are Shokz OpenRun Pro and AfterShokz Aeropex, what are the unsolved technical pain points compared to in-ear earbuds?"
Usage Examples

1. Single-shot AI Overview

json
{
  "keyword": "GaN charger vs traditional charger comparison"
}

2. Cross-border product research

json
{
  "keyword": "best open-ear bone conduction headphones 2026 US"
}

3. Follow-up question (agent summarizes prior result and re-asks in a new call)

First call:

json
{
  "keyword": "best open-ear bone conduction headphones 2026 US"
}

Second call (agent builds context summary + new question):

json
{
  "keyword": "The AI overview mentioned OpenRun Pro and AfterShokz Aeropex as top picks for bone conduction headphones. What unsolved technical pain points still exist compared to in-ear earbuds?"
}

4. Consumer preference snapshot

json
{
  "keyword": "robot vacuum buying preferences 2026 reddit"
}

5. Long-tail keyword exploration for selection

json
{
  "keyword": "smart pet feeder for cats with camera"
}
Show full SKILL.md (510 more words)Show less

Display Rules

  1. Render the Markdown directly: stdout is already structured Markdown with headings, bullets, and citation links — preserve that structure when answering the user.
  2. Cite sources: keep the inline reference links from stdout so the user can verify each claim.
  3. Flag empty AI Overview: if resultsNum is 0, tell the user Google AI Overview did not trigger for that keyword and suggest rephrasing or trying a different region.
  4. Don't reroute to a data-analysis sandbox: the output is unstructured text and not suitable for SQL-like processing.
  5. Indicate freshness: results reflect Google AI Mode at call time; mention this when the user asks about recency.
  6. Handle business errors: if code / errcode is not 200, surface the msg / errmsg to the user and suggest retrying or refining the input.

Important Limitations

  • Unstructured output: Markdown text only — no structured tables, no second-pass data query.
  • AI Overview not guaranteed: some keywords (especially niche, ambiguous, or sensitive ones) do not trigger AI Overview at all (resultsNum = 0).
  • Single-round only: no multi-turn follow-up within one call. For follow-ups, the agent must summarize previous context and make a new call.
  • Locale follows Google's defaults: the tool uses Google's standard AI Mode endpoint without an explicit region switch; bias the language and wording of keyword to match the market you care about.
  • Real-time fetch: results are pulled live, so output for the same keyword can vary across calls.

User Expression & Scenario Quick Reference

Applicable — when the user wants AI-summarized live web information:

User SaysScenario
"用 Google AI 帮我搜...", "Google AI Overview 看下..."Direct AI Overview lookup
"海外消费者对 XX 怎么看", "美国市场对 XX 的偏好"Cross-border consumer preference
"XX 的最新趋势 / 痛点 / 使用场景"Deep research
"顺便问一下 / 然后再追问 ..."Follow-up needed (agent summarizes prior result and re-asks in new call)
"网页上对 XX 的总结", "搜索引擎里大家怎么说 XX"Web-wide summarization
"长尾选品调研 / 蓝海选品方向"Long-tail product exploration

Not applicable — better routed elsewhere:

  • Querying internal structured datasets (use the appropriate data query tool).
  • Amazon ABA search-term analytics (use the ABA data explorer).
  • Pulling structured product listings, prices, reviews from a specific platform (use the matching platform skill).
  • Plain web search where the user only needs raw page content with no AI synthesis (use the standard web search skill).
  • Image generation, image recognition, or file analysis.

Boundary judgment: when the user wants "AI 帮我汇总网上的说法" or "用谷歌搜一下", this skill applies. If the user wants to ask follow-up questions, the agent should summarize the previous answer and make a new call. If they explicitly want raw search results, structured data, or already have a specialized data source, do not use this skill.

算力消耗规则

按动态规则计费：消耗算力 = 对话轮次 × 4.2。

重要：本技能的服务按倍数动态计算，可能一次性消耗大量算力，必须提醒用户，由用户决定是否继续。

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

  1. The functionality or purpose described in this skill does not match actual behavior
  2. The skill's results do not match the user's intent
  3. The user expresses dissatisfaction or praise about this skill
  4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

For more high-quality, professional cross-border e-commerce skills, set LinkFox Skills.

© linkfox-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/linkfox-ai-mode-google-search of linkfox-ai/linkfox-skills.

  • SKILL.md
  • references/api.md
  • references/onboarding.md
  • scripts/google_ai_search.py
  • scripts/onboarding.py

Open the folder on GitHubat commit 38fef04

Compare with similar skills

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Linkfox AI Mode Google Search this skilllinkfox-ai/linkfox-skills107—~2.4kAutomated safety check: PassMIT
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Bmad Deep Recondelorenj/mcp-server-trello445—~2.3kAutomated safety check: PassMIT
Ray Trend Searchimraywang/rayskills159—~2.1kAutomated safety check: PassCustom licence
Argo Search and Verificationtaxueseek/argo188—~1.2kAutomated safety check: PassMIT
Live Researchbrightdata/skills264—~1.8kAutomated safety check: PassMIT

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Categories

Questions about Linkfox AI Mode Google Search

What does Linkfox AI Mode Google Search do?

基于 Google 搜索的 AI 概览（AI Overview / AI Mode）抓取，针对一个关键词返回主搜索的 AI 概览要点，适合用最新网页信息做深度调研、技术问答、长尾选品分析、海外消费者偏好分析。仅支持单轮对话，如需追问须由 agent 总结上下文后发起新请求。当用户提到 Google AI、AI Overview、AI…. Linkfox AI Mode Google Search is an agent skill from linkfox-ai/linkfox-skills.

When should I use Linkfox AI Mode Google Search?

Linkfox AI Mode Google Search fits situations like: tasks that involve AI search optimization; tasks that involve Web search; tasks that involve Deep research.

How do I install Linkfox AI Mode Google Search in Claude Code?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-ai-mode-google-search -a claude-code`. Or copy the skill folder (skills/linkfox-ai-mode-google-search in linkfox-ai/linkfox-skills) into .claude/skills/linkfox-ai-mode-google-search in your project. Claude Code loads it when a task matches its description.

How do I install Linkfox AI Mode Google Search in Codex?

Run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-ai-mode-google-search -a codex`. Or copy the skill folder (skills/linkfox-ai-mode-google-search in linkfox-ai/linkfox-skills) into .agents/skills/linkfox-ai-mode-google-search in your project. Codex loads it when a task matches its description.

Can I use Linkfox AI Mode Google Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add linkfox-ai/linkfox-skills --skill linkfox-ai-mode-google-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkfox-ai-mode-google-search, .gemini/skills/linkfox-ai-mode-google-search, .github/skills/linkfox-ai-mode-google-search and .opencode/skills/linkfox-ai-mode-google-search in your project.

What does Linkfox AI Mode Google Search need to run?

Going by SKILL.md and its folder, Linkfox AI Mode Google Search needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named LINKFOX_AGENT_API_KEY and LINKFOXAGENT_API_KEY. Our summary lists: Python 3; A credential in LINKFOX_AGENT_API_KEY; A credential in LINKFOXAGENT_API_KEY.

Does Linkfox AI Mode Google Search access the network?

SKILL.md names 1 domain. As links in the text: skill.linkfox.com. This is read from the text; nothing was executed.

Is Linkfox AI Mode Google Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Linkfox AI Mode Google Search use?

Linkfox AI Mode Google Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linkfox AI Mode Google Search use?

About 2.4k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Linkfox AI Mode Google Search?

Skills that share tags, products or a category with Linkfox AI Mode Google Search: Web Research (Juncai22/spring-ai-agent-learning, 124 stars), Bmad Deep Recon (delorenj/mcp-server-trello, 445 stars), Ray Trend Search (imraywang/rayskills, 159 stars) and Argo Search and Verification (taxueseek/argo, 188 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linkfox AI Mode Google Search?

linkfox-ai (a GitHub user) maintains it in linkfox-ai/linkfox-skills, which has 107 GitHub stars. The repository holds 177 skills in this directory. The repository was last updated on September 14, 2026.

Source: linkfox-ai/linkfox-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.