agentsclimarketplace

Agent websearch skill

Skill Nex-ZMH/Agent-websearch-skill

智能多引擎搜索,自动检测网络环境并按优先级切换:DuckDuckGo -> Tavily -> Bing API -> Bing爬虫。支持自动配额管理和网络缓存。Invoke when user needs web search with automatic engine selection and network adaptation.From its SKILL.md

Install
npx -y skills add Nex-ZMH/Agent-websearch-skill

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 11 stars11 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

3.7 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it

Multi-Search Skill - 智能多引擎搜索

本技能整合多个搜索引擎,自动检测网络环境,智能选择最佳可用引擎。

引擎优先级

质量优先模式 (prefer_quality=True)

  1. Tavily API (1000次/月) - 质量最高,需 API Key
  2. DuckDuckGo (无限免费) - 无需 API Key
  3. Bing Web Search API (1000次/月) - 需 API Key
  4. Bing 爬虫 (无限免费) - 最终回退

平衡模式 (prefer_quality=False, 默认)

  1. DuckDuckGo (无限免费) - 优先免费引擎
  2. Tavily API (1000次/月) - 如果配置了 API Key
  3. Bing Web Search API (1000次/月)
  4. Bing 爬虫 (无限免费)

核心能力

  • 智能网络检测与引擎切换
  • 自动配额管理(Tavily/Bing API)
  • 支持网页内容抓取
  • 5分钟网络检测缓存

使用方式

基本搜索

from multi_search import search

# 平衡模式 - 优先免费引擎
results = search("Python tutorial", max_results=5)

# 质量优先模式 - 优先使用 Tavily
results = search("AI research", max_results=5, prefer_quality=True)

# 强制重新检测网络(切换 VPN 后使用)
results = search("OpenClaw skills", max_results=5, force_network_check=True)

搜索技能(自动质量优先)

from multi_search import search_skills

results = search_skills("OpenClaw AI agent automation", max_results=10)

查看系统状态

from multi_search import get_status

status = get_status()  # 使用缓存
status = get_status(force_network_check=True)  # 强制重新检测

抓取网页详细内容

from multi_search import search, fetch_web_content, fetch_search_results_content

# 搜索并抓取第一个结果的详细内容
results = search("OpenClaw new features", max_results=3)
if results:
    content = fetch_web_content(results[0]['href'], max_length=3000)
    # content['title'], content['content'], content['success']

# 批量抓取所有搜索结果的详细内容
enriched_results = fetch_search_results_content(results, max_length=2000)
for r in enriched_results:
    if r.get('full_content'):
        # 使用 summarize 技能总结内容
        pass

与 Summarize 技能结合使用

OpenClaw 工作流:
1. 使用 multi-search 搜索关键词
2. 选择感兴趣的搜索结果
3. 使用 fetch_web_content() 抓取网页内容
4. 使用 summarize 技能总结网页内容
5. 将摘要呈现给用户

返回结果格式

[
    {
        'title': '结果标题',
        'href': 'https://example.com',
        'body': '结果摘要...',
        'source': 'duckduckgo'  # 或 'tavily', 'bing_api', 'bing_scraper'
    }
]

参数说明

  • query: 搜索关键词
  • max_results: 最大结果数(默认5)
  • prefer_quality: 是否优先质量(默认False)
  • force_network_check: 是否强制重新检测网络(默认False)

注意事项

  • DuckDuckGo: 免费无限,但某些网络环境无法访问
  • Tavily: 质量高,需要 API key,1000次/月
  • Bing API: 官方稳定,需要 Azure 账号,1000次/月
  • Bing 爬虫: 免费无限,但可能受反爬影响

What ships with it: 8 files

145.5 KB alongside SKILL.md, 1 of them executable

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.