| 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。 |
Google AI Search
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):
- The required
keyword is sent to Google as the query and the AI Overview for it is captured.
- Single-round only: each call handles exactly one question. There is no
prompts parameter for follow-ups.
- 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.
- 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
| Parameter | Type | Required | Description |
|---|
| keyword | string | Yes | Google 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
| Field | Type | Description |
|---|
| stdout | string | Markdown document with the AI Overview for the keyword, plus inline citation links |
| sourceUrl | string | The Google AI Mode search URL that was actually requested |
| resultsNum | integer | Number of AI Overview blocks rendered (0 = keyword did not trigger AI Overview) |
| code / errcode | string / integer | 200 on success; non-200 indicates a business error |
| msg / errmsg | string | ok on success; otherwise an error description |
| costTime | integer | API latency in milliseconds |
| costToken | integer | Tokens consumed (only billed on success) |
| taskId | string | Upstream task identifier for tracing |
| type | string | Render 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：本工具会消耗积分；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。
解决认证和积分问题
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
- 响应提示积分或余额不足：消息含"积分余额不足/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
- 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.
- 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.
- Use natural-language questions: phrasing like "compare against" / "what are the unsolved pain points" elicits richer AI Overview output than single keywords.
- 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
{
"keyword": "GaN charger vs traditional charger comparison"
}
2. Cross-border product research
{
"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:
{
"keyword": "best open-ear bone conduction headphones 2026 US"
}
Second call (agent builds context summary + new question):
{
"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
{
"keyword": "robot vacuum buying preferences 2026 reddit"
}
5. Long-tail keyword exploration for selection
{
"keyword": "smart pet feeder for cats with camera"
}
Display Rules
- Render the Markdown directly:
stdout is already structured Markdown with headings, bullets, and citation links — preserve that structure when answering the user.
- Cite sources: keep the inline reference links from
stdout so the user can verify each claim.
- 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.
- Don't reroute to a data-analysis sandbox: the output is unstructured text and not suitable for SQL-like processing.
- Indicate freshness: results reflect Google AI Mode at call time; mention this when the user asks about recency.
- 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 Says | Scenario |
|---|
| "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.
积分消耗规则
按动态规则计费：消耗积分 = 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积分，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:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
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