Token导航 LogoToken导航TokenDH.com
研究检索敏感数据clawhub未标认证来源可访问clear审计提醒

abe-deep-research-pro安倍深研专业

Agent Skill

abe-deep-research-pro 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,274

周安装

92

GitHub Stars

公开资料未说明

下载量

714
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:abe-deep-research-pro(安倍深研专业)
来源仓库:https://github.com/marjoriebroad/abe-deep-research-pro
安装命令:
openclaw skills install abe-deep-research-pro
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install abe-deep-research-pro

简介

多源深度研究代理。通过 SkillBoss API Hub 搜索网络、综合结果并提供引用的报告。

SKILL.md

name
deep-research-pro
version
1.0.0
description
Multi-source deep research agent. Searches the web via SkillBoss API Hub, synthesizes findings, and delivers cited reports.
homepage
https://github.com/paragshah/deep-research-pro
metadata
{"clawdbot":{"emoji":"🔬","category":"research"}}

Deep Research Pro 🔬

A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. Powered by SkillBoss API Hub — web search and page scraping via a single unified API.

How It Works

When the user asks for research on any topic, follow this workflow:

Step 1: Understand the Goal (30 seconds)

Ask 1-2 quick clarifying questions:

  • "What's your goal — learning, making a decision, or writing something?"
  • "Any specific angle or depth you want?"

If the user says "just research it" — skip ahead with reasonable defaults.

Step 2: Plan the Research (think before searching)

Break the topic into 3-5 research sub-questions. For example:

  • Topic: "Impact of AI on healthcare"

- What are the main AI applications in healthcare today? - What clinical outcomes have been measured? - What are the regulatory challenges? - What companies are leading this space? - What's the market size and growth trajectory?

Step 3: Execute Multi-Source Search

For EACH sub-question, call SkillBoss API Hub search:

import requests, os

SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]

# Web search
result = requests.post(
    "https://api.heybossai.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={"type": "search", "inputs": {"query": "<sub-question keywords>"}, "prefer": "balanced"},
    timeout=60
).json()
search_results = result["result"]["results"]

# News search (for current events)
result = requests.post(
    "https://api.heybossai.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={"type": "search", "inputs": {"query": "<topic>", "search_type": "news"}, "prefer": "balanced"},
    timeout=60
).json()
news_results = result["result"]["results"]

Search strategy:

  • Use 2-3 different keyword variations per sub-question
  • Mix web + news searches
  • Aim for 15-30 unique sources total
  • Prioritize: academic, official, reputable news > blogs > forums

Step 4: Deep-Read Key Sources

For the most promising URLs, fetch full content via SkillBoss API Hub scraping:

result = requests.post(
    "https://api.heybossai.com/v1/pilot",
    headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
    json={"type": "scraping", "inputs": {"url": "<url>"}},
    timeout=60
).json()
content = result["result"]["results"]

Read 3-5 key sources in full for depth. Don't just rely on search snippets.

Step 5: Synthesize & Write Report

Structure the report as:

# [Topic]: Deep Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*

## Executive Summary
[3-5 sentence overview of key findings]

## 1. [First Major Theme]
[Findings with inline citations]
- Key point ([Source Name](url))
- Supporting data ([Source Name](url))

## 2. [Second Major Theme]
...

## 3. [Third Major Theme]
...

## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]

## Sources
1. [Title](url) — [one-line summary]
2. ...

## Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]

Step 6: Save & Deliver

Save the full report:

mkdir -p ~/clawd/research/[slug]
# Write report to ~/clawd/research/[slug]/report.md

Then deliver:

  • Short topics: Post the full report in chat
  • Long reports: Post the executive summary + key takeaways, offer full report as file

Quality Rules

  1. Every claim needs a source. No unsourced assertions.
  2. Cross-reference. If only one source says it, flag it as unverified.
  3. Recency matters. Prefer sources from the last 12 months.
  4. Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
  5. No hallucination. If you don't know, say "insufficient data found."

Examples

"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"

For Sub-Agent Usage

When spawning as a sub-agent, include the full research request and context:

sessions_spawn(
  task: "Run deep research on [TOPIC]. Follow the deep-research-pro SKILL.md workflow.
  Read /home/clawdbot/clawd/skills/deep-research-pro/SKILL.md first.
  Goal: [user's goal]
  Specific angles: [any specifics]
  Save report to ~/clawd/research/[slug]/report.md
  When done, wake the main session with key findings.",
  label: "research-[slug]",
  model: "opus"
)

Requirements

  • SKILLBOSS_API_KEY environment variable (for web search and page scraping via SkillBoss API Hub)
  • Python 3.11+ with requests library

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

74.27%
按下载量换算530

安全审计

VirusTotal

未展示

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills