serper-search

serper-search is a skill for Claude Code, Codex from fanzhidongyzby/openclaw-serper. It costs 55 tokens per session (2,126 once invoked), scanned A, original, MIT.

A web-search skill that uses the Google Serper Search API to find current online information. It supports searches in several languages and regions.

In plain words
What is it for?
Use it to search with focused queries, language or country settings, result limits, and optional time-related terms.
Why use it?
It provides a structured way to look up documentation, news, facts, tutorials, and comparisons instead of relying on memory.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to search with focused queries, language or country settings, result limits, and optional time-related terms.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fanzhidongyzby/openclaw-serper/serper-search
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add fanzhidongyzby/openclaw-serper --skill serper-search
Clone the repo
git clone --depth 1 https://github.com/fanzhidongyzby/openclaw-serper

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for serper-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/fanzhidongyzby/openclaw-serper/serper-search/github.svg)](https://agentmods.dev/skills/fanzhidongyzby/openclaw-serper/serper-search)
Your own site
<a href="https://agentmods.dev/skills/fanzhidongyzby/openclaw-serper/serper-search"><img src="https://agentmods.dev/badge/skills/fanzhidongyzby/openclaw-serper/serper-search/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for serper-search

Your own site · 80×15
<a href="https://agentmods.dev/skills/fanzhidongyzby/openclaw-serper/serper-search"><img src="https://agentmods.dev/badge/skills/fanzhidongyzby/openclaw-serper/serper-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,126 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.02126
Opus 5 $0.00028 $0.01063
Sonnet 5 $0.00011 $0.00425
Haiku 4.5 $0.00006 $0.00213

Measured 12d ago against content hash b8ebe5b1c461, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

serper-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/serper-search/SKILL.md · 300 lines

How it starts

The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Google Serper Search Tool

基于 Google Serper API 的网页搜索工具,提供实时、准确的搜索结果。

When to Activate

当用户提到以下内容时自动激活:

搜索类关键词

  • "搜索"、"搜一下"、"搜搜"、"查找"、"找一下"
  • "研究"、"调研"、"了解"
  • "查询"、"检索"
  • "看看"、"查查"

特定场景

  • 需要获取最新新闻、信息
  • 需要验证事实或数据
  • 需要研究某个技术或概念
  • 需要查找文档、教程
  • 需要比较不同产品或方案

示例问题

  • "搜一下最新的 AI 发展趋势"
  • "帮我搜索最新的 AI 发展趋势"
  • "查找一下 Python 3.13 的新特性"
  • "研究一下自动驾驶技术的现状"
  • "查查最新的网络安全新闻"
  • "找一些关于微服务的教程"

Tools

serper_search

用途: 执行网络搜索,返回结果列表

参数:

  • query (必选,string):搜索关键词
  • num (可选,number):返回结果数量,默认 5,最大 20
  • gl (可选,string):国家代码,默认 cn
  • 推荐值: cn(中国)、us(美国)、uk(英国)、jp(日本)
  • hl (可选,string):语言代码,默认 zh-CN
  • 推荐值: zh-CN(简体中文)、en(英文)、ja(日语)

Best Practices

1. 搜索技巧

使用具体的关键词,避免过于宽泛:

示例:

  • ✅ "Kimi AI 模型 参数 对比 2025"
  • ✅ "Python 3.13 新特性 官方文档"
  • ❌ "Python"(太宽泛,结果太多)

2. 添加时间限定

明确时间范围,获取最新信息:

示例:

  • ✅ "LangChain 最新文档 2025"
  • ✅ "Python 3.13 发布时间"
  • ✅ "AI 人工智能 新闻 2025年2月"

3. 使用精确搜索

用引号搜索精确短语:

示例:

  • ✅ ""machine learning" 最佳实践"
  • ✅ ""RAG 架构" 实现"

4. 添加技术术语

提高搜索精度:

示例:

  • ✅ "Spring Cloud 微服务 实现"
  • ✅ "React Hooks useEffect 使用"

5. 结果数量选择

根据需求调整:

  • 快速查询: num=3(快速浏览核心信息)
  • 深入研究: num=10(全面了解主题)
  • 综合调研: num=20(最大深度,覆盖面广)

6. 多轮搜索策略

对于复杂主题,使用多轮搜索深入挖掘:

场景:研究微服务架构

// 第一轮:基础概念
serper_search({ query: "微服务架构 概念 优势", num: 5 })

// 第二轮:技术实现
serper_search({ query: "微服务 Spring Cloud Kubernetes", num: 8 })

// 第三轮:最佳实践
serper_search({ query: "微服务 最佳实践 常见问题", num: 10 })

7. 结果处理原则

  • 优先权威来源: 官方文档、知名技术博客、学术论文
  • 交叉验证: 对比多个来源的信息
  • 关注时效性: 优先较新的内容(近1-2年)
  • 快速筛选: 通过 snippet 判断相关性

Example Scenarios

场景 1:技术调研

用户提问: "研究一下 LangChain 的核心概念"

AI 行为:

// 搜索核心概念
serper_search({
  query: "LangChain 核心概念 官方文档 2025",
  num: 5
})

// 如果需要更多细节,继续搜索
serper_search({
  query: "LangChain Agents Chains 使用示例",
  num: 8
})

回复示例:

根据搜索结果,LangChain 的核心概念包括:

1. **Chains(链)**:将多个组件串联成工作流
2. **Agents(智能体)**:自主决策的 AI 代理
3. **Tools(工具)**:LLM 可用的外部能力
4. **Memory(记忆)**:对话上下文管理

📖 详细文档:https://python.langchain.com/

Read the full file on GitHub · 300 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 300 lines · 55 tokens per session scan A b8ebe5b1c461

Subscribe to this mod's changes

serper-search is a skill published in the GitHub repository fanzhidongyzby/openclaw-serper (4 stars, last pushed 7mo ago), licensed MIT. It adds 55 tokens to every session and 2,126 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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