explore-agent

explore-agent is an agent for coding agents from LeoYeAI/openclaw-master-skills. It costs 0 tokens per session (1,302 once invoked), scanned A, original, MIT.

A browser-based research agent that searches selected academic databases and returns structured paper metadata. It supports CNKI, Web of Science, ScienceDirect, and PubMed.

In plain words
What is it for?
Use it to search a topic with Chinese or English keywords, run database-specific search expressions, apply year limits, and collect paper information for later review.
Why use it?
It removes the need to repeat searches and copy paper details manually across different research websites. Filters can narrow results by year and maximum number of records.

Agent

About the project

OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.

LeoYeAI/openclaw-master-skills · 2,133 stars · on GitHub · myclaw.ai

Install

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.

agentmods
npx agentmods add agents/leoyeai/openclaw-master-skills/explore-agent
Clone the repo
git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills

Wrote 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.

agentmods badge for explore-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/leoyeai/openclaw-master-skills/explore-agent.svg)](https://agentmods.dev/agents/leoyeai/openclaw-master-skills/explore-agent)
Your own site
<a href="https://agentmods.dev/agents/leoyeai/openclaw-master-skills/explore-agent"><img src="https://agentmods.dev/badge/agents/leoyeai/openclaw-master-skills/explore-agent.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,302 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.01302
Opus 5 $0.00000 $0.00651
Sonnet 5 $0.00000 $0.00260
Haiku 4.5 $0.00000 $0.00130

Measured 2d ago against content hash 668ccd84a6f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

explore-agent 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 2d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/ai-powered-literature-review-skills/agents/explore-agent.md · 189 lines

How it starts

The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Explore Agent 模板

用于在特定学术数据库执行文献检索的Agent。通过浏览器自动化访问数据库检索页面。


Agent 信息

属性
名称 Explore Agent
类型 Task Agent
用途 文献搜索(浏览器自动化)

任务描述

在指定的学术数据库中搜索与给定主题相关的文献,返回结构化的文献元数据列表。

执行方式:使用 browser_navigatebrowser_fill_form 等工具访问数据库网页,提取文献信息。


输入格式

query:
  keywords_zh: ["深度学习", "神经网络"]  # 中文关键词
  keywords_en: ["deep learning", "neural network"]  # 英文关键词
  search_expression_cnki: "SU=('深度学习'+'神经网络')*('医学图像')"
  search_expression_wos: "TS=((deep learning OR neural network) AND medical imaging)"
  
database: "cnki"  # 目标数据库:cnki, wos, sciencedirect, pubmed

filters:
  year_range: [2020, 2025]  # 年份范围
  max_results: 50  # 最大结果数

session_id: "20240115_dl_survey"

支持的数据库

数据库 标识符 访问方式
CNKI 中国知网 cnki 浏览器自动化
Web of Science wos 浏览器自动化
ScienceDirect sciencedirect 浏览器自动化
PubMed pubmed 浏览器自动化

执行步骤

Step 1: 访问数据库检索页面

根据目标数据库访问对应的检索页面:

CNKI:

https://kns.cnki.net/kns8/AdvSearch?classid=YSTT4HG0

Web of Science:

https://www.webofscience.com/wos/woscc/advanced-search

ScienceDirect:

https://www.sciencedirect.com/search

PubMed:

https://pubmed.ncbi.nlm.nih.gov/advanced/

Step 2: 执行检索

  1. 在检索页面填充检索式
  2. 设置筛选条件(年份、文献类型等)
  3. 执行搜索
  4. 等待结果加载

Step 3: 提取文献信息

从搜索结果页面提取以下信息:

  • 标题
  • 作者
  • 期刊/会议名称
  • 年份
  • 卷期页
  • DOI
  • 摘要(如有)

提取示例(使用 browser_evaluate):

// 提取CNKI搜索结果
const papers = [];
const items = document.querySelectorAll('.result-table-list tbody tr');
items.forEach(item => {
  const title = item.querySelector('.title a')?.textContent?.trim();
  const authors = item.querySelector('.author')?.textContent?.trim().split(';');
  const journal = item.querySelector('.source')?.textContent?.trim();
  const year = item.querySelector('.date')?.textContent?.trim();
  papers.push({ title, authors, journal, year });
});
return papers;

Step 4: 格式化输出

Read the full file on GitHub · 189 lines

Changes

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.

  1. 2d ago First seen · 189 lines · 0 tokens per session scan A 668ccd84a6f1

Subscribe to this mod's changes

explore-agent is an agent published in the GitHub repository LeoYeAI/openclaw-master-skills (2,133 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,302 tokens. 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 2026-09-03.