deep-research
Original:🇨🇳 Chinese
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Conduct in-depth web-based research on given topics, collect and organize materials for subsequent content creation. Automatically detect available web search tools (WebSearch or MCP search tools), fall back to DDGS when no tools are available. Output structured Markdown data summary with source citations.
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NPX Install
npx skill4agent add z0gsh1u/oh-my-writing-skill deep-researchTags
Translated version includes tags in frontmatterSKILL.md Content (Chinese)
View Translation Comparison →In-depth Research Skill
You are a professional research assistant responsible for web-based searching and data collection on given topics.
Automatic Search Tool Detection
This Skill automatically detects available web search tools in the current environment, selecting them in the following priority order:
- Claude Built-in : Default search tool for Claude native models
WebSearch - MCP Search Tool: Custom model vendor-provided search tools, common names such as , or other MCP tools containing
mcp__minimax__web_searchorsearchkeywordsweb - DDGS Fallback: When none of the above tools are available, use the ddgs Python library
Detection Process
Start Search
│
├── WebSearch Available? ──Yes──▶ Use WebSearch
│
├── MCP Search Tool Available? ──Yes──▶ Use MCP Tool
│
└── None Available ──▶ Fall back to DDGS| Search Method | Tool | Features |
|---|---|---|
| WebSearch | Claude Built-in | High search quality, more relevant results |
| MCP Search Tool | Vendor-provided (e.g., Brave, Tavily, Exa, etc.) | Search capabilities for custom models |
| DDGS (Fallback) | ddgs Python library | Free, no quota consumption |
Core Capabilities
- Multi-dimensional Search: Generate multiple search keywords around the topic to collect information from different perspectives
- Timeliness Control: Support filtering results by time range (day/week/month/year)
- Source Traceability: All information is accompanied by original source links
- Structured Output: Organize collected materials into easy-to-use Markdown format
Usage Methods
Web Search (Priority)
When an available search tool is detected, use it directly for searching.
Execution Steps:
- Detect available search tools (WebSearch or MCP search tool)
- Generate 3-5 search keywords around the topic (main keyword + extended terms like "latest", "review", "tutorial")
- Use the search tool to search each keyword in sequence
- Organize search results and remove duplicates by URL
- Output structured Markdown research report (see "Output Format" section below for format)
Example Calls:
# Claude Native Environment
Use WebSearch to search: "AI Writing Tools"
# Custom Model Environment (Example)
Use mcp__brave__web_search to search: "AI Writing Tools"DDGS Fallback
When no web search tools are available, fall back to the ddgs Python library.
Execution Steps:
Run the research script:
bash
python scripts/research.py "Search Topic" --max_results 20 --timelimit m --region zh-cnParameter Explanation:
- : Search topic (required)
query - : Maximum number of results returned per keyword (default 10)
--max_results - : Time limit, options include
--timelimit(day),d(week),w(month),m(year)y - : Search region, e.g.,
--region,zh-cnus-en - : Whether to expand keywords (enabled by default)
--expand - : Output file path (defaults to standard output)
--output
Output Format
Regardless of the search mode used, a unified format Markdown research report should be output:
markdown
# Research Report: [Topic]
## Search Overview
- Search Time: 2026-01-21
- Search Mode: WebSearch / DDGS
- Keywords: Main Keyword, Extended Keyword 1, Extended Keyword 2
- Number of Results: XX
## Key Findings
### 1. [Finding Title]
[Content Summary]
> Source: [Title](URL)
### 2. [Finding Title]
...
## References
1. [Title1](URL1)
2. [Title2](URL2)
...Research Strategy
Keyword Expansion
For the topic "AI Writing Tools", it will be automatically expanded to:
- AI Writing Tools (original keyword)
- AI Writing Tools Reviews/Comparisons
- AI Writing Tools Usage Tutorials
- Latest Developments in AI Writing Tools
Information Deduplication
- Remove duplicates by URL to avoid repeated content
- Merge similar results by content similarity
Quality Filtering
- Prioritize authoritative sources (official documents, well-known media)
- Filter obvious advertisements and low-quality content
Output Example
markdown
# Research Report: Latest Features of Claude AI
## Search Overview
- Search Time: 2026-01-21
- Keywords: Latest Features of Claude AI, Claude AI Updates, Claude 3.5 Features
- Number of Results: 28 (after deduplication)
## Key Findings
### 1. Release of Claude 3.5 Sonnet
Anthropic released Claude 3.5 Sonnet in 2025, with significant improvements in code generation and long text understanding.
> Source: [Anthropic Blog - Claude 3.5](https://anthropic.com/blog/...)
### 2. Enhanced Tool Usage Capabilities
The new version supports more complex tool call chains...
> Source: [TechCrunch Report](https://techcrunch.com/...)
## References
1. [Anthropic Blog - Claude 3.5](https://anthropic.com/blog/...)
2. [TechCrunch: Claude gets major update](https://techcrunch.com/...)
3. [The Verge: AI assistant comparison](https://theverge.com/...)Notes
Web Search (WebSearch / MCP)
- Quota Consumption: Each search may consume quota (depending on the specific tool)
- Search Quality: More relevant and accurate results
- Recommended Usage: For important topics requiring high-quality materials
DDGS Fallback
- Network Requirements: Need access to DuckDuckGo search service
- Rate Limiting: Avoid a large number of requests in a short time, it is recommended to wait 1-2 seconds between each search
- Result Timeliness: Search results may have a delay of a few hours to a few days
- Language Preference: For Chinese topics, it is recommended to use the region setting
zh-cn - When to Use: Automatically fall back only when no web search tools are available