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.
npx skills add qingkongzhiqian/groundapi --skill groundapi-web-researchergit clone --depth 1 https://github.com/qingkongzhiqian/groundapiWrote 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.
[](https://agentmods.dev/skills/qingkongzhiqian/groundapi/groundapi-web-researcher)<a href="https://agentmods.dev/skills/qingkongzhiqian/groundapi/groundapi-web-researcher"><img src="https://agentmods.dev/badge/skills/qingkongzhiqian/groundapi/groundapi-web-researcher/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.
<a href="https://agentmods.dev/skills/qingkongzhiqian/groundapi/groundapi-web-researcher"><img src="https://agentmods.dev/badge/skills/qingkongzhiqian/groundapi/groundapi-web-researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.01068 |
| Opus 5 | $0.00022 | $0.00534 |
| Sonnet 5 | $0.00009 | $0.00214 |
| Haiku 4.5 | $0.00004 | $0.00107 |
Grade A, and why
groundapi-web-researcher 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 10d 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.
What it actually says
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(oneWeek 或 oneDay)。
Step 3 — 筛选与综合
从搜索结果中挑选最相关、最权威的 3-5 个条目(优先选择:官方来源 > 权威媒体 > 行业报告 > 博客),基于 snippet 摘要进行综合。
由于摘要长度有限,建议针对同一话题用不同关键词组合多搜几轮,以获得更全面的信息。
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:
- 对每个对比对象分别搜索
- 抓取各自最相关的 2-3 篇内容
- 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
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.
- 10d ago First seen · 128 lines · 44 tokens per session scan A c81b3eb37c46
groundapi-web-researcher is a skill published in the GitHub repository qingkongzhiqian/groundapi (0 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 1,068 once invoked, about $0.0002 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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