Groundapi Web Researcher

v1.1.0

Deep web research assistant — search, scrape, check trending topics, get daily briefings, and synthesize information from multiple sources into a structured...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for qingkongzhiqian/groundapi-web-researcher.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Groundapi Web Researcher" (qingkongzhiqian/groundapi-web-researcher) from ClawHub.
Skill page: https://clawhub.ai/qingkongzhiqian/groundapi-web-researcher
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: GROUNDAPI_KEY
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install groundapi-web-researcher

ClawHub CLI

Package manager switcher

npx clawhub@latest install groundapi-web-researcher
Security Scan
Capability signals
Requires sensitive credentials
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description (web research, searching, scraping, trending, briefings) match the declared requirement: a single GroundAPI API key and calls to GroundAPI MCP endpoints. No unrelated services, binaries, or unusual config paths are requested.
Instruction Scope
SKILL.md instructs the agent to call GroundAPI MCP methods (info_search, info_scrape, info_trending, info_bulletin) and to select/summarize sources. It does not instruct reading local files, other env vars, or sending data to third-party endpoints outside the GroundAPI MCP URL shown. It explicitly warns not to scrape paywalled content and to cite sources.
Install Mechanism
No install spec or code files are present; this is an instruction-only skill so nothing will be downloaded or written to disk by an installer.
Credentials
Only one credential is required (GROUNDAPI_KEY) and that aligns with calling a hosted GroundAPI MCP service. The SKILL.md example shows an API key header, which is consistent with the declared primaryEnv.
Persistence & Privilege
always:false and normal autonomous invocation settings. The skill does not request persistent system-wide changes or access to other skills' credentials.
Assessment
This skill appears internally consistent, but before installing: 1) Verify you trust https://groundapi.net and its MCP endpoint (review privacy, terms, and what data they retain). 2) Provide a scoped API key (GROUNDAPI_KEY) with minimal permissions if possible, and rotate/revoke it if you stop using the skill. 3) Be aware the skill performs web scraping via the GroundAPI service — avoid sending sensitive or private URLs you don't want processed by a third party. 4) Because the skill can be invoked by the agent, monitor agent activity and logs for unexpected requests to the MCP endpoint. If you need more assurance, ask the vendor for documented API behavior and a list of endpoints the MCP server will contact on your behalf.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🌐 Clawdis
EnvGROUNDAPI_KEY
Primary envGROUNDAPI_KEY
latestvk973mteecavj7catyydzwhbp2h84x7bm
165downloads
0stars
2versions
Updated 1w ago
v1.1.0
MIT-0

网络调研助手

当用户需要对某个话题做深入了解,或类似以下表达时自动触发:

  • "帮我调研一下 XXX"、"查一下 XXX 的情况"
  • "XXX 的最新进展是什么"、"帮我了解一下 XXX"
  • "对比一下 A 和 B"、"总结一下这个话题"
  • "帮我搜一下..."、"研究一下..."
  • "现在什么最火"、"今天有什么热点"

前置条件

本 Skill 依赖 GroundAPI MCP Server 提供的工具。确保已配置 GroundAPI MCP 连接:

{
  "mcpServers": {
    "groundapi": {
      "url": "https://mcp.groundapi.net/mcp",
      "headers": {
        "X-API-Key": "sk_gapi_xxxxx"
      }
    }
  }
}

执行流程

Step 1 — 拆解调研问题

将用户的调研需求拆解为 1-3 个搜索查询,覆盖不同角度。

示例:用户说"帮我调研一下固态电池的发展现状"

  • 查询 1:固态电池 技术进展 2026(技术角度)
  • 查询 2:固态电池 产业链 公司 量产(产业角度)
  • 查询 3:固态电池 市场规模 预测(市场角度)

Step 1.5 — 热度预判(可选)

调用 info_trending() 查看该话题是否在全网热搜中,了解当前舆论热度。 调用 info_bulletin() 获取每日新闻简报,看该话题是否在今日重点事件中。

如果话题正在热搜,优先使用 recency="oneDay" 获取最新信息。

Step 2 — 搜索

对每个查询调用 info_search(query="...", count=10, recency="oneMonth")

如果话题有时效性或正在热搜中,使用更短的 recency(oneWeekoneDay)。

Step 3 — 筛选与抓取

从搜索结果中挑选最相关、最权威的 3-5 个链接(优先选择:官方来源 > 权威媒体 > 行业报告 > 博客),调用 info_scrape(url="...") 获取全文。

如果某个 URL 抓取失败,跳过并使用搜索摘要代替。

Step 4 — 综合输出

## 🌐 调研报告:{话题}

### 概述
(2-3 句话的核心结论)

### 关键发现

**1. {角度一标题}**
- 要点 A(来源:XXX)
- 要点 B(来源:XXX)

**2. {角度二标题}**
- 要点 A(来源:XXX)
- 要点 B(来源:XXX)

**3. {角度三标题}**
- 要点 A(来源:XXX)
- 要点 B(来源:XXX)

### 总结与观点
(基于多源信息的综合判断,标注哪些是事实、哪些是推测)

### 信息来源
1. [标题](URL) — 简要说明
2. [标题](URL) — 简要说明
3. ...

对比调研模式

当用户要求对比两个或多个事物时(如"对比 React 和 Vue"),调整流程:

  1. 对每个对比对象分别搜索
  2. 抓取各自最相关的 2-3 篇内容
  3. 按统一维度做对比表格输出:
### 对比:A vs B

| 维度 | A | B |
|------|---|---|
| 维度1 | ... | ... |
| 维度2 | ... | ... |
| ... |

### 结论
(根据使用场景给出建议)

注意事项

  • 始终标注信息来源,不要把不同来源的信息混在一起而不注明
  • 区分"事实"(有明确数据支撑)和"观点"(来自分析/预测)
  • 如果搜索结果质量不佳或信息过少,如实告知用户,不要编造内容
  • 抓取网页时尊重内容:不要抓取明显需要付费阅读的内容
  • 输出语言跟随用户

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