Web Research Documenter

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:

1. Formulate search query based on user's topic and language
2. Use web_search tool with appropriate max_results (typically 8-12)
3. 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:

1. 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)

2. Use fetch tool 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

3. 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:

1. Header: Title, date, topic overview
2. Executive Summary: 2-3 paragraph overview in user's language
3. Main Content: Organized sections with clear headings
   • Use numbered sections or topic-based organization
   • Include subheadings for clarity
4. Key Points: Important findings, data, or insights
5. Context: Background information, current state, significance
6. Conclusion: Key takeaways and synthesis
7. 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:

1. Confirm file path from user request
   • Use absolute paths when provided
   • Default to /tmp/ if no path specified and ask user for confirmation
2. Use write_file tool with mode='rewrite'
3. Include the complete structured document from Phase 3
4. 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 .txt or .md extensions 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:

1. Phase 1 - Search:

   • Query: "Python 머신러닝 라이브러리 최신 트렌드 2024"
   • Results: 10 sources about ML libraries, frameworks, trends

2. Phase 2 - Fetch:

   • Fetch 2-3 Korean or English sources with detailed ML library information
   • Extract: Library names, usage statistics, new features, comparison data

3. 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

4. Phase 4 - Save:

   • Write to: /Users/user/Documents/ml_trends.txt
   • Confirm: "✅ 머신러닝 라이브러리 트렌드 리포트가 저장되었습니다!"

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