| name | web-research-documenter |
| description | This skill should be used when users request research on any topic that requires web search, source analysis, and structured documentation saved to a file. It provides a systematic workflow for gathering information from multiple web sources, synthesizing findings into a comprehensive document, and saving results to a user-specified file path. This is a general-purpose research skill that works across all domains and languages. |
Web Research Documenter
Overview
This skill provides a systematic workflow for researching any topic by conducting web searches, analyzing authoritative sources, synthesizing information into well-structured documents, and saving results to user-specified file paths. Unlike domain-specific research skills, this is a general-purpose skill that works across all topics and supports multiple languages.
When to Use This Skill
Use this skill when users request:
- Research on any topic with file output
- Information gathering from web sources
- Structured documentation of findings
- Topic summaries or reports
- Multi-source analysis and synthesis
Trigger patterns include:
- "[Topic]을/를 검색하고 파일로 저장해줘" (Korean)
- "Research [topic] and save to file"
- "Search for [topic] and create a report"
- "Find information about [topic] and document it"
- "Investigate [topic] and save the summary"
Key indicators:
- Request involves web search/research
- Request specifies file output or saving results
- Request requires synthesis from multiple sources
- Request asks for structured documentation
Workflow
Follow this systematic four-phase workflow:
Phase 1: Initial Web Search
Conduct broad web search to identify key themes and authoritative sources.
Steps:
- Formulate search query based on user's topic and language
- Use
web_searchtool with appropriatemax_results(typically 8-12) - Scan results to identify:
- Major themes and key information
- Authoritative sources
- Specific data points or statistics
- Key terminology and concepts
Search Query Guidelines:
- Match the user's language (if user asks in Korean, search in Korean)
- Include temporal indicators when relevant: "2024", "2025", "latest", "recent", "최신"
- Add context keywords based on topic type
- Be specific but not overly narrow
- Examples:
- Good: "TypeScript 최신 트렌드 2024 2025"
- Good: "climate change latest research 2024"
- Good: "人工智能发展趋势 2024" (Chinese example)
- Too narrow: "TypeScript 5.3.2 bug fixes"
- Too broad: "technology"
Available parameters:
await web_search({
"query": "search terms here",
"max_results": 10, # default: 10
"engine": "duckduckgo" # default, can also use "brave" or "serper"
})
Phase 2: Deep Source Analysis
Fetch and analyze 2-4 most relevant sources for detailed information.
Steps:
Select sources based on:
- Recency (prefer recent content when researching trends)
- Authority (official sources, major publications, recognized experts)
- Comprehensiveness (detailed content over brief mentions)
- Relevance to user's specific question
- Language match (prefer sources in user's language when available)
Use
fetchtool to retrieve full content:- Set appropriate
max_length(6000-10000 for detailed articles) - Fetch multiple sources when possible
- Handle fetch failures gracefully (some sites may block access)
- Prioritize sources that provide different perspectives
- Set appropriate
Extract key information:
- Main points and themes
- Specific data, statistics, or metrics
- Expert opinions or authoritative statements
- Examples or case studies
- Future predictions or trends
Available parameters:
await fetch({
"url": "https://example.com/article",
"max_length": 8000, # default: 5000
"start_index": 0, # default: 0
"raw": False # default: False (returns markdown)
})
Handling fetch failures:
- If a source fails to fetch, continue with other sources
- Log the failure but don't let it stop the workflow
- Ensure at least 2 sources are successfully fetched
- If all fetches fail, synthesize from search results only
Phase 3: Information Synthesis
Organize and synthesize information into a structured document.
Language Matching:
- CRITICAL: Match the document language to the user's request language
- If user asks in Korean, write the entire document in Korean
- If user asks in English, write in English
- If user asks in another language, write in that language
- Maintain consistency throughout the document
Structure Guidelines:
Core sections to include:
- Header: Title, date, topic overview
- Executive Summary: 2-3 paragraph overview in user's language
- Main Content: Organized sections with clear headings
- Use numbered sections or topic-based organization
- Include subheadings for clarity
- Key Points: Important findings, data, or insights
- Context: Background information, current state, significance
- Conclusion: Key takeaways and synthesis
- References: Source links and citations
Formatting Standards:
- Use clear hierarchy: Headers with
===, subheaders with---, bullet points - Include specific data: percentages, dates, numbers, names
- Provide examples when relevant
- Add visual separation: line breaks, section dividers
- Use symbols for emphasis: ✓, •, →, ★, 📌
- Keep paragraphs concise: 3-5 sentences maximum
- Use lists and bullet points for readability
Content Quality Standards:
- Accuracy: Verify claims across multiple sources
- Completeness: Cover all major themes identified in Phase 1
- Balance: Include multiple perspectives when available
- Specificity: Avoid vague statements; provide concrete details
- Clarity: Write in clear, accessible language
- Attribution: Cite sources for key claims and data
Document Length:
- Aim for comprehensive but readable documents
- Typical range: 150-250 lines for thorough research
- Adjust based on topic complexity and user needs
- Better to be thorough than superficial
Phase 4: File Documentation
Save the synthesized document to the user's specified file path.
Steps:
- Confirm file path from user request
- Use absolute paths when provided
- Default to
/tmp/if no path specified and ask user for confirmation
- Use
write_filetool withmode='rewrite' - Include the complete structured document from Phase 3
- Confirm successful save to user
Available parameters:
await write_file({
"path": "/absolute/path/to/file.txt",
"content": "Document content here...",
"mode": "rewrite" # or "append"
})
File Naming Conventions:
- Use descriptive names based on topic
- Include date if relevant:
topic_2024.txt - Use underscores for spaces:
climate_research.txt - Prefer
.txtor.mdextensions for text documents - Match user's specified filename if provided
Best Practices
Search Strategy
- Cast wide net first: Initial search should be broad to capture full picture
- Multiple angles: Consider different search terms for comprehensive coverage
- Language awareness: Search in the user's language when possible
- Validate recency: Check publication dates when researching current topics
Source Selection
- Quality over quantity: Better to have 2-3 excellent sources than 5 mediocre ones
- Diversity: Seek different perspectives and types of sources
- Authority: Prioritize official sources, experts, and reputable publications
- Accessibility: Some sources may block fetch; have backup options
Synthesis Quality
- Structure matters: Well-organized content is more valuable than comprehensive chaos
- Context is key: Explain significance and implications, not just facts
- Be objective: Present balanced view and acknowledge limitations
- Stay focused: Address user's question directly; avoid tangents
Language and Localization
- Match user's language: If user asks in Korean, respond in Korean
- Maintain consistency: Don't mix languages within the document
- Cultural context: Consider cultural relevance when selecting sources
- Clear translation: When sources are in different languages, integrate smoothly
Common Pitfalls to Avoid
- Stopping too early: Don't rely only on initial search results
- Language mismatch: Don't respond in English when user asks in another language
- Poor structure: Avoid walls of text; use clear organization
- Missing attribution: Always cite sources for key information
- Ignoring failures: Handle fetch failures gracefully and continue
- Vague content: Provide specific information and concrete details
Quality Checklist
Before saving the file, verify:
- ✓ Document language matches user's request language
- ✓ All major themes from initial search are covered
- ✓ At least 2 authoritative sources were analyzed
- ✓ Specific data points and examples are included
- ✓ Document follows clear structural format
- ✓ Content is well-formatted with headers and organization
- ✓ Conclusion provides meaningful synthesis
- ✓ Sources are cited in references section
- ✓ File path is correct (absolute path)
- ✓ No placeholder text or incomplete sections
Workflow Example
User Request: "Python 머신러닝 라이브러리 트렌드를 조사해서 ~/Documents/ml_trends.txt로 저장해줘"
Execution:
Phase 1 - Search:
- Query: "Python 머신러닝 라이브러리 최신 트렌드 2024"
- Results: 10 sources about ML libraries, frameworks, trends
Phase 2 - Fetch:
- Fetch 2-3 Korean or English sources with detailed ML library information
- Extract: Library names, usage statistics, new features, comparison data
Phase 3 - Synthesize:
- Write document in Korean (matching user's language)
- Structure: 개요 → 주요 라이브러리 트렌드 → 비교 분석 → 결론
- Include: TensorFlow, PyTorch, scikit-learn statistics and trends
- Format: Clear headers, bullet points, data points
Phase 4 - Save:
- Write to:
/Users/user/Documents/ml_trends.txt - Confirm: "✅ 머신러닝 라이브러리 트렌드 리포트가 저장되었습니다!"
- Write to:
Cross-Domain Adaptability
This skill works across all domains and topics:
Technology: Programming languages, frameworks, tools, trends Science: Research findings, discoveries, methodologies Business: Market analysis, industry trends, company research Health: Medical research, treatments, health trends Culture: Arts, entertainment, social trends Education: Learning resources, educational trends, courses Current Events: News, developments, ongoing situations Any topic: The workflow adapts to any research subject
Multi-Language Support
This skill supports research in any language:
- Korean: Full support for Korean queries and Korean documents
- English: Full support for English queries and English documents
- Other languages: Adaptable to any language (Chinese, Japanese, Spanish, etc.)
- Mixed sources: Can synthesize from sources in multiple languages
- Language matching: Always match output language to user's request language
Notes
- Objectivity: Present balanced, factual information
- Timeliness: Check publication dates for time-sensitive topics
- User's language: Always match the document language to user's request
- File permissions: Verify user has write access to specified path
- Follow-up: Be prepared to expand or clarify sections if user requests
- Flexibility: Adapt structure and depth based on topic and user needs