openclaw-aisa-search-web-academic-tavily
Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API.
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install openclaw-aisa-search-web-academic-tavily或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install openclaw-aisa-search-web-academic-tavily⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/openclaw-aisa-search-web-academic-tavily/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: openclaw-search description: "Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API." homepage: https://openclaw.ai metadata: {"openclaw":{"emoji":"🔍","requires":{"bins":["curl","python3"],"env":["AISA_API_KEY"]},"primaryEnv":"AISA_API_KEY"}} ---
Intelligent search for autonomous agents. Powered by AIsa.
One API key. Multi-source retrieval. Confidence-scored answers.
> Inspired by AIsa Verity - A next-generation search agent with trust-scored answers.
"Search for the latest papers on transformer architectures from 2024-2025"
"Find all web articles about AI startup funding in Q4 2025"
"Search for reviews and comparisons of RAG frameworks"
"Get the latest news about quantum computing breakthroughs"
"Smart search combining web and academic sources on 'autonomous agents'"
export AISA_API_KEY="your-key"
---
OpenClaw Search employs a Two-Phase Retrieval Strategy for comprehensive results:
Query 4 distinct search streams simultaneously:
Use AIsa Explain to perform meta-analysis on search results, generating:
┌─────────────────────────────────────────────────────────────┐
│ User Query │
└─────────────────────────────────────────────────────────────┘
│
┌───────────────┼───────────────┐
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Scholar │ │ Web │ │ Smart │
└─────────┘ └─────────┘ └─────────┘
│ │ │
└───────────────┼───────────────┘
▼
┌─────────────────┐
│ AIsa Explain │
│ (Meta-Analysis) │
└─────────────────┘
│
▼
┌─────────────────┐
│ Confidence Score│
│ + Synthesis │
└─────────────────┘
---
# Basic web search
curl -X POST "https://api.aisa.one/apis/v1/scholar/search/web?query=AI+frameworks&max_num_results=10" \
-H "Authorization: Bearer $AISA_API_KEY"
# Full text search (with page content)
curl -X POST "https://api.aisa.one/apis/v1/search/full?query=latest+AI+news&max_num_results=10" \
-H "Authorization: Bearer $AISA_API_KEY"
# Search academic papers
curl -X POST "https://api.aisa.one/apis/v1/scholar/search/scholar?query=transformer+models&max_num_results=10" \
-H "Authorization: Bearer $AISA_API_KEY"
# With year filter
curl -X POST "https://api.aisa.one/apis/v1/scholar/search/scholar?query=LLM&max_num_results=10&as_ylo=2024&as_yhi=2025" \
-H "Authorization: Bearer $AISA_API_KEY"
# Intelligent hybrid search
curl -X POST "https://api.aisa.one/apis/v1/scholar/search/smart?query=machine+learning+optimization&max_num_results=10" \
-H "Authorization: Bearer $AISA_API_KEY"
# Tavily search
curl -X POST "https://api.aisa.one/apis/v1/tavily/search" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"query":"latest AI developments"}'
# Extract content from URLs
curl -X POST "https://api.aisa.one/apis/v1/tavily/extract" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"urls":["https://example.com/article"]}'
# Crawl web pages
curl -X POST "https://api.aisa.one/apis/v1/tavily/crawl" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://example.com","max_depth":2}'
# Site map
curl -X POST "https://api.aisa.one/apis/v1/tavily/map" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://example.com"}'
# Generate explanations with confidence scoring
curl -X POST "https://api.aisa.one/apis/v1/scholar/explain" \
-H "Authorization: Bearer $AISA_API_KEY" \
-H "Content-Type: application/json" \
-d '{"results":[...],"language":"en","format":"summary"}'
---
Unlike standard RAG systems, OpenClaw Search evaluates credibility and consensus:
| Factor | Weight | Description | |--------|--------|-------------| | Source Quality | 40% | Academic > Smart/Web > External | | Agreement Analysis | 35% | Cross-source consensus checking | | Recency | 15% | Newer sources weighted higher | | Relevance | 10% | Query-result semantic match |
| Score | Confidence Level | Meaning | |-------|-----------------|---------| | 90-100 | Very High | Strong consensus across academic and web sources | | 70-89 | High | Good agreement, reliable sources | | 50-69 | Medium | Mixed signals, verify independently | | 30-49 | Low | Conflicting sources, use caution | | 0-29 | Very Low | Insufficient or contradictory data |
---
# Web search
python3 {baseDir}/scripts/search_client.py web --query "latest AI news" --count 10
# Academic search
python3 {baseDir}/scripts/search_client.py scholar --query "transformer architecture" --count 10
python3 {baseDir}/scripts/search_client.py scholar --query "LLM" --year-from 2024 --year-to 2025
# Smart search (web + academic)
python3 {baseDir}/scripts/search_client.py smart --query "autonomous agents" --count 10
# Full text search
python3 {baseDir}/scripts/search_client.py full --query "AI startup funding"
# Tavily operations
python3 {baseDir}/scripts/search_client.py tavily-search --query "AI developments"
python3 {baseDir}/scripts/search_client.py tavily-extract --urls "https://example.com/article"
# Multi-source search with confidence scoring
python3 {baseDir}/scripts/search_client.py verity --query "Is quantum computing ready for enterprise?"
---
| Endpoint | Method | Description |
|----------|--------|-------------|
| /scholar/search/web | POST | Web search with structured results |
| /scholar/search/scholar | POST | Academic paper search |
| /scholar/search/smart | POST | Intelligent hybrid search |
| /scholar/explain | POST | Generate result explanations |
| /search/full | POST | Full text search with content |
| /search/smart | POST | Smart web search |
| /tavily/search | POST | Tavily search integration |
| /tavily/extract | POST | Extract content from URLs |
| /tavily/crawl | POST | Crawl web pages |
| /tavily/map | POST | Generate site maps |
---
| Parameter | Type | Description | |-----------|------|-------------| | query | string | Search query (required) | | max_num_results | integer | Max results (1-100, default 10) | | as_ylo | integer | Year lower bound (scholar only) | | as_yhi | integer | Year upper bound (scholar only) |
---
...
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将技能文件夹放到 ~/.claude/skills/openclaw-aisa-search-web-academic-tavily/ 目录(个人级,所有项目可用),或 .claude/skills/openclaw-aisa-search-web-academic-tavily/(项目级)。重启 AI 客户端后,用 /openclaw-aisa-search-web-academic-tavily 主动调用,或让 AI 根据上下文自动发现并使用。
Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API 可免费安装使用。请查阅仓库了解许可证信息。
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Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API.
Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API 属于「Data & Analytics」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。