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Deep Research Pro 1.0.2

作者 Raidan Pro · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
222
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5
当前安装
1
版本数
在 OpenClaw 中安装
/install deep-research-pro-1-0-2
功能描述
Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.
使用说明 (SKILL.md)

Deep Research Pro 🔬

A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. No paid APIs required — uses DuckDuckGo search.

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, run the DDG search script:

# Web search
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg "\x3Csub-question keywords>" --max 8

# News search (for current events)
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg news "\x3Ctopic>" --max 5

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:

curl -sL "\x3Curl>" | python3 -c "
import sys, re
html = sys.stdin.read()
# Strip tags, get text
text = re.sub('\x3C[^>]+>', ' ', html)
text = re.sub(r'\s+', ' ', text).strip()
print(text[:5000])
"

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

  • DDG search script: /home/clawdbot/clawd/skills/ddg-search/scripts/ddg
  • curl (for fetching full pages)
  • No API keys needed!
安全使用建议
This skill's SKILL.md hard-codes execution of a local ddg search script (/home/clawdbot/.../ddg) and uses curl/python3 but fails to declare those dependencies. Before installing: 1) Inspect the actual ddg script at the path referenced (if it exists) to verify what it runs — it could execute arbitrary commands. 2) Confirm curl and python3 are the intended tools and that running curl | python3 is acceptable in your environment. 3) Ask the author to (a) declare required binaries and config paths in metadata, (b) avoid hard-coded absolute paths or provide a packaged ddg-search dependency, or (c) switch to an explicit network API call or a bundled, auditable search implementation. 4) Run the skill in a restricted/sandboxed environment first and monitor filesystem and network activity. If you cannot inspect the ddg script or the environment where it will run, treat this skill as risky and avoid granting it execution privileges.
功能分析
Type: OpenClaw Skill Name: deep-research-pro-1-0-2 Version: 1.0.0 The skill is a legitimate research tool designed to perform web searches via DuckDuckGo and synthesize reports. It uses standard command-line utilities like curl and python3 for web scraping and file operations for saving reports, all of which are consistent with its stated purpose in SKILL.md.
能力评估
Purpose & Capability
The skill claims to perform web research using DuckDuckGo with no API keys, which fits the description; however the runtime instructions require a local ddg search script at /home/clawdbot/clawd/skills/ddg-search/scripts/ddg and use curl/python3. None of these binaries or config paths are listed in the skill's declared requirements, and the ddg script appears to be a dependency provided by another skill (not declared). Hard-coded absolute paths to another skill's script are disproportionate and fragile.
Instruction Scope
SKILL.md instructs the agent to execute commands against absolute local paths (/home/clawdbot/...), run a local ddg script, fetch arbitrary URLs with curl and pipe them into python3 -c, create directories under ~/clawd/research, and spawn sub-agents reading local skill files. These instructions reference system paths and other skills' files not declared in the metadata and grant the agent discretion to fetch and process many external URLs — all of which broaden the runtime surface beyond what's documented.
Install Mechanism
There is no install spec (instruction-only), which reduces direct install risk. However, relying on an undeclared local script (ddg) and standard tools (curl, python3) means the skill expects existing software on the host; because the script path is an arbitrary local file, execution of that script (if present) could run anything. No external downloads are specified.
Credentials
The skill requests no credentials or environment variables, which is proportionate. That said, it omits declaring required binaries (curl, python3) and required config paths (/home/clawdbot/... and ~/clawd/...), so the metadata understates what the skill actually needs and will access.
Persistence & Privilege
The skill is not set to always:true and is user-invocable (defaults). It directs saving reports under the user's home (~/clawd/research) and instructs spawning sub-agents, which are normal for a research agent. There is no explicit request to modify other skills' configurations or to remain permanently enabled.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install deep-research-pro-1-0-2
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /deep-research-pro-1-0-2 触发
  4. 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
Deep Research Pro 1.0.0 - Initial release of a self-contained, multi-source web research agent. - Guides users through a detailed workflow: clarifies research goals, breaks topics into sub-questions, performs comprehensive web and news searches, and synthesizes findings into a cited, structured report. - Prioritizes source quality and recency; includes strict fact-checking and cross-referencing rules. - No paid APIs or API keys required—uses DuckDuckGo for search and curl for content retrieval. - Supports both in-chat summaries and full markdown report files based on topic length.
元数据
Slug deep-research-pro-1-0-2
版本 1.0.0
许可证 MIT-0
累计安装 5
当前安装数 5
历史版本数 1
常见问题

Deep Research Pro 1.0.2 是什么?

Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 222 次。

如何安装 Deep Research Pro 1.0.2?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install deep-research-pro-1-0-2」即可一键安装,无需额外配置。

Deep Research Pro 1.0.2 是免费的吗?

是的,Deep Research Pro 1.0.2 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Deep Research Pro 1.0.2 支持哪些平台?

Deep Research Pro 1.0.2 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 Deep Research Pro 1.0.2?

由 Raidan Pro(@raidan-ai)开发并维护,当前版本 v1.0.0。

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