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在 OpenClaw 中安装
/install liang-tavily-research
功能描述
Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, d...
使用说明 (SKILL.md)
Tavily Research
Conduct comprehensive research on any topic with automatic source gathering, analysis, and response generation with citations.
Authentication
Get your API key at https://tavily.com and add to your OpenClaw config:
{
"skills": {
"entries": {
"tavily-research": {
"enabled": true,
"apiKey": "tvly-YOUR_API_KEY_HERE"
}
}
}
}
Or set the environment variable:
export TAVILY_API_KEY="tvly-YOUR_API_KEY_HERE"
Quick Start
Using the Script
node {baseDir}/scripts/research.mjs "query"
node {baseDir}/scripts/research.mjs "query" --pro
node {baseDir}/scripts/research.mjs "query" --output report.md
Examples
# Quick overview
node {baseDir}/scripts/research.mjs "What is retrieval augmented generation?"
# Comprehensive analysis
node {baseDir}/scripts/research.mjs "LangGraph vs CrewAI for multi-agent systems" --pro
# Market research with output file
node {baseDir}/scripts/research.mjs "Fintech startup landscape 2025" --pro --output fintech-report.md
# Technical comparison
node {baseDir}/scripts/research.mjs "React vs Vue vs Svelte" --pro
Options
| Option | Description | Default |
|---|---|---|
--model \x3Cmodel> |
Model: mini, pro, auto |
mini |
--output \x3Cfile> |
Save report to file | - |
--json |
Output raw JSON | false |
Model Selection
Rule of thumb: "what does X do?" → mini. "X vs Y vs Z" or "best way to..." → pro.
| Model | Use Case | Speed |
|---|---|---|
mini |
Single topic, targeted research | ~30s |
pro |
Comprehensive multi-angle analysis | ~60-120s |
auto |
API chooses based on complexity | Varies |
Output Format
The research includes:
- AI-generated answer: Comprehensive synthesis
- Sources: Citations with titles, URLs, and relevance scores
- Metadata: Query, response time, and statistics
Tips
- Research can take 30-120 seconds depending on complexity
- Use
--profor comparisons, market analysis, or detailed reports - Use
--outputto save reports for later reference - The
automodel lets Tavily choose based on query complexity
安全使用建议
This skill appears to do exactly what it says: it sends your query to Tavily's API and formats the response. Before installing, confirm you trust tavily.com and are comfortable providing your Tavily API key to the agent (the key is used to authenticate requests to api.tavily.com). If you have sensitive queries, avoid using --output to save them to disk in shared locations. If you need stricter controls, consider creating a limited-scope API key (if Tavily supports that) or reviewing network policies so the skill can only contact api.tavily.com.
功能分析
Type: OpenClaw Skill
Name: liang-tavily-research
Version: 1.0.0
The skill provides a wrapper for the Tavily API, allowing research queries and outputting results. The `scripts/research.mjs` script includes an `--output <file>` option that directly uses the provided file path with `fs.writeFileSync` without any path sanitization. This creates a vulnerability where an AI agent, if prompted by a malicious user or if its own logic is flawed, could be instructed to write the research report to an arbitrary file path (e.g., via path traversal), potentially overwriting sensitive files or leading to further compromise. While the feature of saving a report is legitimate, the lack of input validation for the file path constitutes a high-risk capability.
能力评估
Purpose & Capability
Name/description (web research with citations) align with required items: Node runtime and a single TAVILY_API_KEY. The script sends queries to api.tavily.com and returns results, which is consistent with the stated functionality.
Instruction Scope
SKILL.md and the included script limit actions to: reading TAVILY_API_KEY, POSTing a JSON query to https://api.tavily.com/search, formatting the returned JSON into a report, and optionally writing the report to a file. There are no instructions to read other environment variables, scan local files, or transmit data to third-party endpoints.
Install Mechanism
No install spec is provided (instruction-only plus an included script). The only runtime requirement is the node binary, which is reasonable for a JS script. Nothing is downloaded from untrusted URLs or written to unusual locations.
Credentials
Only one credential is required (TAVILY_API_KEY) and it is the primary credential. That matches the need to authenticate to Tavily's API; there are no unrelated secrets or broad environment access requested.
Persistence & Privilege
always is false and the skill does not request persistent system-wide changes or modify other skills. It does not store credentials itself; it expects the user to provide the API key via env or config.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install liang-tavily-research - 安装完成后，直接呼叫该 Skill 的名称或使用
/liang-tavily-research触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
tavily-research 1.0.0 – Initial release
- Enables comprehensive web-based research with explicit citations.
- Supports both quick overviews and detailed multi-source synthesis (comparisons, market analysis, current events).
- Allows interactive queries via command line with options for output file, model selection, and JSON output.
- Includes authentication via API key and clear instructions for setup.
- Provides flexible model choices: mini, pro, and auto, to suit various research needs.
元数据
常见问题
Tavily Research 是什么？
Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, d... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 574 次。
如何安装 Tavily Research？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install liang-tavily-research」即可一键安装，无需额外配置。
Tavily Research 是免费的吗？
是的，Tavily Research 完全免费（开源免费），可自由下载、安装和使用。
Tavily Research 支持哪些平台？
Tavily Research 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Tavily Research？
由 Liang（@matthew77）开发并维护，当前版本 v1.0.0。
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