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Deep Research

by nb-clh · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install agentic-rag-cn
Description
Deep web research across 11 Chinese and international sources (Baidu, Bing, Sogou, Quark, ChinaSo, WeChat, Yandex, Zhihu, Bilibili, V2EX, GitHub). Use when t...
README (SKILL.md)

Deep Research

Search across 11 sources simultaneously via a local Agentic RAG-CN API, then synthesize results with evidence tables and contradiction detection.

Prerequisites

Agentic RAG-CN must be running locally. Check with:

curl -s http://localhost:18888/health

If unavailable, fall back to built-in web_search tool.

Usage

Call the API with a POST request:

curl -s -X POST http://localhost:18888/api/analyze \
  -H "Content-Type: application/json" \
  -d '{"question": "用户的问题"}'

Parse the JSON response and present results to the user in a readable format.

Response Format

The API returns:

  • answer — Structured answer with evidence tables
  • sources — List of sources used (with URLs)
  • confidence — Confidence score (0-1)
  • contradictions — Any contradictions found across sources
  • trace — Pipeline execution trace (16 steps)

When to Use vs Fallback

Condition Action
API health check succeeds Use deep-research API
API health check fails Fall back to web_search
User asks about Chinese topics (知乎, B站, 微信) Prefer deep-research
User asks general English questions web_search is usually sufficient

Presenting Results

Format the response as:

  1. Answer summary — 2-3 sentences
  2. Evidence table — Key findings with sources
  3. Contradictions (if any) — Highlight conflicting info
  4. Sources — Numbered list of URLs
Usage Guidance
Treat this as an incomplete review: the requested workspace inspection failed before metadata.json or artifact files could be read, so installation should wait for a successful artifact review.
Capability Assessment
Purpose & Capability
Not assessable from artifacts because metadata.json and artifact contents could not be read in this run.
Instruction Scope
Not assessable from artifacts because the local inspection command failed before SKILL.md or related files could be reviewed.
Install Mechanism
Not assessable from artifacts because install metadata and file contents could not be inspected.
Credentials
Not assessable from artifacts because capability and runtime evidence was unavailable.
Persistence & Privilege
Not assessable from artifacts because persistence, credential, and privilege instructions could not be inspected.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install agentic-rag-cn
  3. After installation, invoke the skill by name or use /agentic-rag-cn
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: 11-source deep search (Baidu, Bing, Sogou, Quark, ChinaSo, WeChat, Yandex, Zhihu, Bilibili, V2EX, GitHub) via Agentic RAG-CN
Metadata
Slug agentic-rag-cn
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Deep Research?

Deep web research across 11 Chinese and international sources (Baidu, Bing, Sogou, Quark, ChinaSo, WeChat, Yandex, Zhihu, Bilibili, V2EX, GitHub). Use when t... It is an AI Agent Skill for Claude Code / OpenClaw, with 41 downloads so far.

How do I install Deep Research?

Run "/install agentic-rag-cn" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Deep Research free?

Yes, Deep Research is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Deep Research support?

Deep Research is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Deep Research?

It is built and maintained by nb-clh (@nb-clh); the current version is v1.0.0.

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