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# Deep Research Prompt Generator Instructions
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< critical > The workflow execution engine is governed by: {project_root}/bmad/core/tasks/workflow.xml< / critical >
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< critical > You MUST have already loaded and processed: {installed_path}/workflow.yaml< / critical >
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< critical > This workflow uses ADAPTIVE FACILITATION - adjust your communication style based on {user_skill_level}< / critical >
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< critical > This workflow generates structured research prompts optimized for AI platforms< / critical >
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< critical > Based on {{current_year}} best practices from ChatGPT, Gemini, Grok, and Claude< / critical >
< critical > Communicate all responses in {communication_language} and tailor to {user_skill_level}< / critical >
< critical > Generate all documents in {document_output_language}< / critical >
< critical > 🚨 BUILD ANTI-HALLUCINATION INTO PROMPTS 🚨< / critical >
< critical > Generated prompts MUST instruct AI to cite sources with URLs for all factual claims< / critical >
< critical > Include validation requirements: "Cross-reference claims with at least 2 independent sources"< / critical >
< critical > Add explicit instructions: "If you cannot find reliable data, state 'No verified data found for [X]'"< / critical >
< critical > Require confidence indicators in prompts: "Mark each claim with confidence level and source quality"< / critical >
< critical > Include fact-checking instructions: "Distinguish between verified facts, analysis, and speculation"< / critical >
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< workflow >
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< step n = "1" goal = "Discover what research prompt they need" >
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< action > Engage conversationally to understand their needs:
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< check if = "{user_skill_level} == 'expert'" >
"Let's craft a research prompt optimized for AI deep research tools.
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What topic or question do you want to investigate, and which platform are you planning to use? (ChatGPT Deep Research, Gemini, Grok, Claude Projects)"
< / check >
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< check if = "{user_skill_level} == 'intermediate'" >
"I'll help you create a structured research prompt for AI platforms like ChatGPT Deep Research, Gemini, or Grok.
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These tools work best with well-structured prompts that define scope, sources, and output format.
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What do you want to research?"
< / check >
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< check if = "{user_skill_level} == 'beginner'" >
"Think of this as creating a detailed brief for an AI research assistant.
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Tools like ChatGPT Deep Research can spend hours searching the web and synthesizing information - but they work best when you give them clear instructions about what to look for and how to present it.
What topic are you curious about?"
< / check >
< / action >
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< action > Through conversation, discover:
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- **The research topic** - What they want to explore
- **Their purpose** - Why they need this (decision-making, learning, writing, etc.)
- **Target platform** - Which AI tool they'll use (affects prompt structure)
- **Existing knowledge** - What they already know vs. what's uncertain
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Adapt your questions based on their clarity:
- If they're vague → Help them sharpen the focus
- If they're specific → Capture the details
- If they're unsure about platform → Guide them to the best fit
Don't make them fill out a form - have a real conversation.
< / action >
< template-output > research_topic< / template-output >
< template-output > research_goal< / template-output >
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< template-output > target_platform< / template-output >
< / step >
< step n = "2" goal = "Define Research Scope and Boundaries" >
< action > Help user define clear boundaries for focused research< / action >
**Let's define the scope to ensure focused, actionable results:**
< ask > **Temporal Scope** - What time period should the research cover?
- Current state only (last 6-12 months)
- Recent trends (last 2-3 years)
- Historical context (5-10 years)
- Future outlook (projections 3-5 years)
- Custom date range (specify)</ ask >
< template-output > temporal_scope< / template-output >
< ask > **Geographic Scope** - What geographic focus?
- Global
- Regional (North America, Europe, Asia-Pacific, etc.)
- Specific countries
- US-focused
- Other (specify)</ ask >
< template-output > geographic_scope< / template-output >
< ask > **Thematic Boundaries** - Are there specific aspects to focus on or exclude?
Examples:
- Focus: technological innovation, regulatory changes, market dynamics
- Exclude: historical background, unrelated adjacent markets</ ask >
< template-output > thematic_boundaries< / template-output >
< / step >
< step n = "3" goal = "Specify Information Types and Sources" >
< action > Determine what types of information and sources are needed< / action >
**What types of information do you need?**
< ask > Select all that apply:
- [ ] Quantitative data and statistics
- [ ] Qualitative insights and expert opinions
- [ ] Trends and patterns
- [ ] Case studies and examples
- [ ] Comparative analysis
- [ ] Technical specifications
- [ ] Regulatory and compliance information
- [ ] Financial data
- [ ] Academic research
- [ ] Industry reports
- [ ] News and current events</ ask >
< template-output > information_types< / template-output >
< ask > **Preferred Sources** - Any specific source types or credibility requirements?
Examples:
- Peer-reviewed academic journals
- Industry analyst reports (Gartner, Forrester, IDC)
- Government/regulatory sources
- Financial reports and SEC filings
- Technical documentation
- News from major publications
- Expert blogs and thought leadership
- Social media and forums (with caveats)</ ask >
< template-output > preferred_sources< / template-output >
< / step >
< step n = "4" goal = "Define Output Structure and Format" >
< action > Specify desired output format for the research< / action >
< ask > **Output Format** - How should the research be structured?
1. Executive Summary + Detailed Sections
2. Comparative Analysis Table
3. Chronological Timeline
4. SWOT Analysis Framework
5. Problem-Solution-Impact Format
6. Question-Answer Format
7. Custom structure (describe)</ ask >
< template-output > output_format< / template-output >
< ask > **Key Sections** - What specific sections or questions should the research address?
Examples for market research:
- Market size and growth
- Key players and competitive landscape
- Trends and drivers
- Challenges and barriers
- Future outlook
Examples for technical research:
- Current state of technology
- Alternative approaches and trade-offs
- Best practices and patterns
- Implementation considerations
- Tool/framework comparison</ ask >
< template-output > key_sections< / template-output >
< ask > **Depth Level** - How detailed should each section be?
- High-level overview (2-3 paragraphs per section)
- Standard depth (1-2 pages per section)
- Comprehensive (3-5 pages per section with examples)
- Exhaustive (deep dive with all available data)</ ask >
< template-output > depth_level< / template-output >
< / step >
< step n = "5" goal = "Add Context and Constraints" >
< action > Gather additional context to make the prompt more effective< / action >
< ask > **Persona/Perspective** - Should the research take a specific viewpoint?
Examples:
- "Act as a venture capital analyst evaluating investment opportunities"
- "Act as a CTO evaluating technology choices for a fintech startup"
- "Act as an academic researcher reviewing literature"
- "Act as a product manager assessing market opportunities"
- No specific persona needed</ ask >
< template-output > research_persona< / template-output >
< ask > **Special Requirements or Constraints:**
- Citation requirements (e.g., "Include source URLs for all claims")
- Bias considerations (e.g., "Consider perspectives from both proponents and critics")
- Recency requirements (e.g., "Prioritize sources from 2024-2025")
- Specific keywords or technical terms to focus on
- Any topics or angles to avoid</ ask >
< template-output > special_requirements< / template-output >
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< invoke-task halt = "true" > {project-root}/bmad/core/tasks/adv-elicit.xml< / invoke-task >
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< / step >
< step n = "6" goal = "Define Validation and Follow-up Strategy" >
< action > Establish how to validate findings and what follow-ups might be needed< / action >
< ask > **Validation Criteria** - How should the research be validated?
- Cross-reference multiple sources for key claims
- Identify conflicting viewpoints and resolve them
- Distinguish between facts, expert opinions, and speculation
- Note confidence levels for different findings
- Highlight gaps or areas needing more research</ ask >
< template-output > validation_criteria< / template-output >
< ask > **Follow-up Questions** - What potential follow-up questions should be anticipated?
Examples:
- "If cost data is unclear, drill deeper into pricing models"
- "If regulatory landscape is complex, create separate analysis"
- "If multiple technical approaches exist, create comparison matrix"</ ask >
< template-output > follow_up_strategy< / template-output >
< / step >
< step n = "7" goal = "Generate Optimized Research Prompt" >
< action > Synthesize all inputs into platform-optimized research prompt< / action >
< critical > Generate the deep research prompt using best practices for the target platform< / critical >
**Prompt Structure Best Practices:**
1. **Clear Title/Question** (specific, focused)
2. **Context and Goal** (why this research matters)
3. **Scope Definition** (boundaries and constraints)
4. **Information Requirements** (what types of data/insights)
5. **Output Structure** (format and sections)
6. **Source Guidance** (preferred sources and credibility)
7. **Validation Requirements** (how to verify findings)
8. **Keywords** (precise technical terms, brand names)
< action > Generate prompt following this structure< / action >
< template-output file = "deep-research-prompt.md" > deep_research_prompt< / template-output >
< ask > Review the generated prompt:
- [a] Accept and save
- [e] Edit sections
- [r] Refine with additional context
- [o] Optimize for different platform</ ask >
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< check if = "edit or refine" >
< ask > What would you like to adjust?< / ask >
< goto step = "7" > Regenerate with modifications< / goto >
< / check >
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< / step >
< step n = "8" goal = "Generate Platform-Specific Tips" >
< action > Provide platform-specific usage tips based on target platform< / action >
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< check if = "target_platform includes ChatGPT" >
**ChatGPT Deep Research Tips:**
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- Use clear verbs: "compare," "analyze," "synthesize," "recommend"
- Specify keywords explicitly to guide search
- Answer clarifying questions thoroughly (requests are more expensive)
- You have 25-250 queries/month depending on tier
- Review the research plan before it starts searching
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< / check >
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< check if = "target_platform includes Gemini" >
**Gemini Deep Research Tips:**
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- Keep initial prompt simple - you can adjust the research plan
- Be specific and clear - vagueness is the enemy
- Review and modify the multi-point research plan before it runs
- Use follow-up questions to drill deeper or add sections
- Available in 45+ languages globally
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< / check >
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< check if = "target_platform includes Grok" >
**Grok DeepSearch Tips:**
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- Include date windows: "from Jan-Jun 2025"
- Specify output format: "bullet list + citations"
- Pair with Think Mode for reasoning
- Use follow-up commands: "Expand on [topic]" to deepen sections
- Verify facts when obscure sources cited
- Free tier: 5 queries/24hrs, Premium: 30/2hrs
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< / check >
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< check if = "target_platform includes Claude" >
**Claude Projects Tips:**
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- Use Chain of Thought prompting for complex reasoning
- Break into sub-prompts for multi-step research (prompt chaining)
- Add relevant documents to Project for context
- Provide explicit instructions and examples
- Test iteratively and refine prompts
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< / check >
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< template-output > platform_tips< / template-output >
< / step >
< step n = "9" goal = "Generate Research Execution Checklist" >
< action > Create a checklist for executing and evaluating the research< / action >
Generate execution checklist with:
**Before Running Research:**
- [ ] Prompt clearly states the research question
- [ ] Scope and boundaries are well-defined
- [ ] Output format and structure specified
- [ ] Keywords and technical terms included
- [ ] Source guidance provided
- [ ] Validation criteria clear
**During Research:**
- [ ] Review research plan before execution (if platform provides)
- [ ] Answer any clarifying questions thoroughly
- [ ] Monitor progress if platform shows reasoning process
- [ ] Take notes on unexpected findings or gaps
**After Research Completion:**
- [ ] Verify key facts from multiple sources
- [ ] Check citation credibility
- [ ] Identify conflicting information and resolve
- [ ] Note confidence levels for findings
- [ ] Identify gaps requiring follow-up
- [ ] Ask clarifying follow-up questions
- [ ] Export/save research before query limit resets
< template-output > execution_checklist< / template-output >
< / step >
< step n = "10" goal = "Finalize and Export" >
< action > Save complete research prompt package< / action >
**Your Deep Research Prompt Package is ready!**
The output includes:
1. **Optimized Research Prompt** - Ready to paste into AI platform
2. **Platform-Specific Tips** - How to get the best results
3. **Execution Checklist** - Ensure thorough research process
4. **Follow-up Strategy** - Questions to deepen findings
< action > Save all outputs to {default_output_file}< / action >
< ask > Would you like to:
1. Generate a variation for a different platform
2. Create a follow-up prompt based on hypothetical findings
3. Generate a related research prompt
4. Exit workflow
Select option (1-4):< / ask >
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< check if = "option 1" >
< goto step = "1" > Start with different platform selection< / goto >
< / check >
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< check if = "option 2 or 3" >
< goto step = "1" > Start new prompt with context from previous< / goto >
< / check >
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< / step >
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< step n = "FINAL" goal = "Update status file on completion" tag = "workflow-status" >
< check if = "standalone_mode != true" >
< action > Load the FULL file: {output_folder}/bmm-workflow-status.yaml< / action >
< action > Find workflow_status key "research"< / action >
< critical > ONLY write the file path as the status value - no other text, notes, or metadata< / critical >
< action > Update workflow_status["research"] = "{output_folder}/bmm-research-deep-prompt-{{date}}.md"< / action >
< action > Save file, preserving ALL comments and structure including STATUS DEFINITIONS< / action >
< action > Find first non-completed workflow in workflow_status (next workflow to do)< / action >
< action > Determine next agent from path file based on next workflow< / action >
< / check >
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< output > **✅ Deep Research Prompt Generated**
**Research Prompt:**
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- Structured research prompt generated and saved to {output_folder}/bmm-research-deep-prompt-{{date}}.md
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- Ready to execute with ChatGPT, Claude, Gemini, or Grok
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{{#if standalone_mode != true}}
**Status Updated:**
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- Progress tracking updated: research marked complete
- Next workflow: {{next_workflow}}
{{else}}
**Note:** Running in standalone mode (no progress tracking)
{{/if}}
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**Next Steps:**
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{{#if standalone_mode != true}}
- **Next workflow:** {{next_workflow}} ({{next_agent}} agent)
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- **Optional:** Execute the research prompt with AI platform, gather findings, or run additional research workflows
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Check status anytime with: `workflow-status`
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{{else}}
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Since no workflow is in progress:
- Execute the research prompt with AI platform and gather findings
- Refer to the BMM workflow guide if unsure what to do next
- Or run `workflow-init` to create a workflow path and get guided next steps
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{{/if}}
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< / output >
< / step >
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< / workflow >