Deep Research Query Builder

Transform vague research ideas into structured, actionable research queries.

Trigger Conditions

# Primary triggers
- "/deep-research query"
- "리서치 쿼리 만들어줘"
- "research query builder"
- "structured research query"
- "쿼리 빌더"

WHEN TRIGGERED - EXECUTE IMMEDIATELY

Phase 1: Discovery (REQUIRED)

EXECUTE: 아래 JSON으로 AskUserQuestion 도구를 즉시 호출한다. Detect user language and translate all labels.

{
  "questions": [
    {
      "question": "What topic do you want to research?",
      "header": "Topic",
      "options": [
        {"label": "Type your topic", "description": "Enter a specific research topic or question"},
        {"label": "Browse examples", "description": "See example queries for inspiration"}
      ],
      "multiSelect": false
    },
    {
      "question": "What type of research is this?",
      "header": "Type",
      "options": [
        {"label": "Exploratory", "description": "Discover what exists, map the landscape"},
        {"label": "Comparative", "description": "Compare technologies, approaches, or products"},
        {"label": "Analytical", "description": "Deep analysis of causes, effects, and mechanisms"},
        {"label": "Predictive", "description": "Future trends, forecasts, and projections"}
      ],
      "multiSelect": false
    }
  ]
}

If user selects "Browse examples", load and present examples from: ${CLAUDE_PLUGIN_ROOT}/skills/deep-research-main/examples/

Phase 2: Detailed Scoping

After getting the core topic, EXECUTE: 아래 JSON으로 AskUserQuestion 도구를 즉시 호출한다:

{
  "questions": [
    {
      "question": "What geographic scope?",
      "header": "Geography",
      "options": [
        {"label": "Global", "description": "Worldwide perspective"},
        {"label": "US/North America", "description": "Focus on United States and North America"},
        {"label": "Asia-Pacific", "description": "Focus on APAC region"},
        {"label": "Europe", "description": "Focus on European markets"}
      ],
      "multiSelect": false
    },
    {
      "question": "What source quality do you need?",
      "header": "Quality",
      "options": [
        {"label": "A - Academic only", "description": "Peer-reviewed papers, meta-analyses only"},
        {"label": "B - High quality (Recommended)", "description": "Academic + official docs + established reports"},
        {"label": "C - Moderate", "description": "Include expert opinions and case studies"},
        {"label": "D - Broad coverage", "description": "Include preprints and expert blogs for maximum coverage"}
      ],
      "multiSelect": false
    }
  ]
}

Phase 3: Query Generation

After gathering all inputs, generate:

Structured JSON Query following the schema at: ${CLAUDE_PLUGIN_ROOT}/skills/deep-research-query/references/query_schema.json
Human-Readable Research Brief in markdown format
Execution Checklist for quality verification

Output Format

JSON Query Structure

{
  "task": {
    "title": "[Concise 5-15 word title]",
    "objective": "[Clear statement of research goal]",
    "type": "exploratory|comparative|analytical|predictive|evaluative"
  },
  "context": {
    "background": "[Why this research matters]",
    "audience": "technical|executive|academic|general|policy_maker",
    "use_case": "[How the research will be used]",
    "prior_knowledge": ["assumption 1", "assumption 2"]
  },
  "questions": {
    "primary": "[Main research question]",
    "secondary": ["Sub-question 1", "Sub-question 2", "Sub-question 3"],
    "hypotheses": ["Testable assumption 1"],
    "exclusions": ["Out of scope topic 1"]
  },
  "constraints": {
    "timeframe": {"start": "2024-01-01", "end": "present", "focus_period": "2025-2026"},
    "geography": {"scope": "global", "regions": [], "exclude_regions": []},
    "sources": {
      "required_types": ["peer_reviewed", "industry_reports"],
      "min_quality": "B",
      "language": ["en"]
    }
  },
  "output": {
    "format": "comprehensive_report",
    "length": {"min_words": 3000, "max_words": 10000},
    "structure": {
      "include_executive_summary": true,
      "include_bibliography": true,
      "generate_website": false
    },
    "citation_style": "APA",
    "tone": "professional"
  },
  "keywords": ["keyword1", "keyword2"],
  "special_instructions": []
}

Human-Readable Brief

# Research Brief: [Title]

## Objective
[Clear statement]

## Research Questions
### Primary Question
> [Main question]

### Secondary Questions
1. [Sub-question 1]
2. [Sub-question 2]

## Scope & Constraints
| Dimension | Specification |
|-----------|--------------|
| Timeframe | [period] |
| Geography | [scope] |
| Min Quality | Grade [X] |

## Execution Checklist
- [ ] Primary question fully answered
- [ ] All secondary questions addressed
- [ ] Sources meet quality threshold
- [ ] Citations properly formatted

Phase 4: Confirmation and Handoff

EXECUTE: 아래 JSON으로 AskUserQuestion 도구를 즉시 호출한다:

{
  "questions": [
    {
      "question": "Query looks good? Ready to start research?",
      "header": "Action",
      "options": [
        {"label": "Start research now", "description": "Launch deep research with this query immediately"},
        {"label": "Save query only", "description": "Save the JSON query for later use"},
        {"label": "Adjust query", "description": "Modify some parameters before starting"}
      ],
      "multiSelect": false
    }
  ]
}

Start research now -> Pass the JSON query to deep-research-main skill
Save query only -> Write the JSON to a file for the user
Adjust query -> Loop back to gather adjustments

Quality Validation Rules

Before finalizing the query, verify:

Task Validation

Title is specific (not generic like "AI Research")
Objective is measurable/verifiable
Type matches the research approach

Questions Validation

Primary question is answerable (not too broad)
Secondary questions support primary (not tangential)
Exclusions prevent scope creep

Constraints Validation

Timeframe is realistic for the topic
Geography matches topic relevance
Source requirements are achievable

Output Validation

Length matches depth requested
Format suits the audience

Anti-Patterns to Avoid

DO NOT Generate:

Overly broad questions ("What is AI?")
Unbounded timeframes ("all history")
Conflicting constraints
Generic keywords ("technology", "innovation")
Unmeasurable objectives ("understand everything about...")

DO Generate:

Specific, answerable questions ("What is the current adoption rate of AI diagnostic tools in US hospitals?")
Realistic scope boundaries (2-3 year timeframe for fast-moving fields)
Concrete success criteria ("Identify top 10 tools by market share")
Actionable search terms ("AI radiology FDA approved 2024 2025 adoption rate")
Clear exclusions ("Exclude consumer health apps and administrative AI")

Example Transformation

Input (Vague)

"I want to know about AI in healthcare"

Discovery Process

After Phase 1-2 questions, the vague input transforms into:

Dimension	Vague	Structured
Title	"AI in healthcare"	"AI Diagnostic Systems in Clinical Healthcare: Adoption and Impact 2023-2026"
Scope	Everything	US hospitals, diagnostic AI only, 2023-present
Exclusions	None	Consumer apps, billing AI, drug discovery
Sources	Any	FDA databases, PubMed, Gartner reports
Metrics	None	Adoption rate %, sensitivity/specificity, ROI timeline

Generated Keywords

From the vague "AI healthcare", generate specific search terms:

"AI diagnostics FDA approved 2025"
"clinical AI adoption rate hospital"
"radiology AI sensitivity specificity study"
"healthcare AI ROI implementation cost"
"medical AI regulatory compliance HIPAA"

Language Adaptation

All AskUserQuestion labels and descriptions adapt to the user's detected language.

Korean Input Handling

When user inputs Korean (e.g., "헬스케어 AI 리서치 쿼리 만들어줘"):

All question labels in Korean
Geographic options include Korea-relevant choices
Source options include Korean research databases
Output includes Korean citation conventions

Multi-language Keywords

Generate search keywords in both the user's language and English for maximum coverage:

Korean input: "AI 의료 진단"
Generated: ["AI 의료 진단 2026", "AI medical diagnostics 2026", "의료 AI 도입 현황", "clinical AI adoption"]

Integration with Deep Research

The generated query feeds directly into the deep-research-main skill:

Query builder outputs structured JSON
User confirms or adjusts
If "Start research now" selected, the JSON is passed to deep-research-main
Phase 1 (Question Scoping) is skipped since requirements are already defined
Research begins from Phase 2 (Retrieval Planning)

Save location for queries: RESEARCH/queries/{topic}_{timestamp}.json

References

Query schema: ${CLAUDE_PLUGIN_ROOT}/skills/deep-research-query/references/query_schema.json
Example queries: ${CLAUDE_PLUGIN_ROOT}/skills/deep-research-main/examples/

deep-research-query