| name | market-researcher |
| description | God-level internet research and data synthesis for any topic. Use when the user wants to research, compare, analyze, or find the best options for anything: business ideas, products (phones, laptops, gadgets), services (credit cards, banks, insurance), travel (hotels, flights, destinations), market trends, industry data, competitor analysis, pricing comparisons, consumer reviews, emerging opportunities, or any general-purpose research task. Triggers on: 'research', 'find the best', 'compare', 'what's the best', 'top 10', 'under X price', 'market data', 'industry trends', 'alternatives to', 'reviews of', or any request requiring internet research and data gathering. |
Market Researcher
Transform any research question into structured, actionable intelligence with verified data, source attribution, and clear recommendations.
Core Research Process
Every research task follows this workflow:
User Question
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1. SCOPE → Define what exactly needs answering
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2. SEARCH → Gather data from multiple sources
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3. VERIFY → Cross-reference and validate findings
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4. SYNTHESIZE → Organize into structured insights
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5. DELIVER → Present with sources and recommendations
Step 1: Scope the Research
Before searching, clarify the research boundaries:
Identify the research type:
| Type | Example | Approach |
|---|
| Product comparison | "Best laptop under $1000" | Feature matrix + price-value scoring |
| Service evaluation | "Best credit cards for travel" | Benefits comparison + cost analysis |
| Market analysis | "AI industry trends 2026" | Data aggregation + trend mapping |
| Opportunity research | "Business ideas in health tech" | Market gap analysis + viability scoring |
| Location/travel | "Best hotels in Tokyo" | Rating aggregation + value scoring |
| Competitor analysis | "Alternatives to Notion" | Feature parity + differentiation mapping |
| General inquiry | "How does X work?" | Multi-source synthesis + expert consensus |
Define constraints explicitly:
- Budget range (if applicable)
- Geography/region
- Time sensitivity (current data vs. historical)
- User's experience level (beginner vs. expert)
- Priority factors (price vs. quality vs. speed vs. features)
If constraints are unclear, ask. One focused question beats five assumptions.
Step 2: Search Strategy
Source Priority Hierarchy
Prioritize sources in this order:
- Primary data — Official websites, government databases, SEC filings, patent databases, published research papers
- Authoritative aggregators — Industry reports (Gartner, Statista, IBISWorld), financial databases (Bloomberg, Yahoo Finance), review aggregators (Wirecutter, Consumer Reports)
- Expert content — Domain-specific publications, verified expert analyses, peer-reviewed journals, established trade publications
- Community intelligence — Reddit threads (sorted by top/best), Stack Exchange, Quora (verified authors), specialized forums
- News and media — Recent articles from established outlets, press releases, conference coverage
- Social signals — Trending topics, user sentiment, social media discussions (lowest reliability, use for directional signals only)
Search Techniques
Breadth-first for discovery:
- Search the broad topic to understand the landscape
- Identify key players, categories, and dimensions
- Note recurring recommendations and patterns across multiple sources
Depth-first for validation:
- Drill into top candidates with specific queries
- Cross-reference claims across independent sources
- Look for disconfirming evidence (negative reviews, limitations, complaints)
Temporal awareness:
- Always check publication dates — outdated data kills research quality
- For products: specs and pricing change rapidly, verify current availability
- For markets: use the most recent data available, note the data vintage
- Flag when information may be stale
Research Depth Calibration
| Request Complexity | Sources to Check | Time Investment |
|---|
| Quick comparison (2-3 items) | 3-5 sources | Light |
| Thorough comparison (5-10 items) | 8-12 sources | Medium |
| Market analysis | 10-20 sources | Deep |
| Industry deep-dive | 20+ sources | Comprehensive |
Step 3: Verify and Validate
The Three-Source Rule
Never present a claim backed by only one source. Minimum verification:
- Facts and statistics → Confirm with 3+ independent sources
- Product claims → Cross-reference specs from manufacturer AND third-party reviewers
- Market data → Triangulate from multiple research firms or data providers
- Pricing → Verify from official source + at least one independent price tracker
- Expert opinions → Present as opinions, not facts; note consensus vs. dissent
Red Flags to Watch For
- Affiliate-heavy "review" sites (prioritize unbiased sources)
- Outdated information presented as current
- Single-source claims repeated across multiple sites (echo chamber)
- Sponsored content disguised as editorial
- Survivorship bias (only successful examples shown)
- Small sample sizes extrapolated to broad conclusions
Data Quality Tags
Tag every data point with confidence level:
- HIGH — Official sources, verified data, multiple confirmations
- MEDIUM — Reputable single source, expert opinion, recent but unconfirmed
- LOW — Anecdotal, single user report, potentially outdated
- ESTIMATED — Calculated or inferred from available data
Step 4: Synthesize Findings
Structure by Research Type
For product/service comparisons — See references/comparison-templates.md
For market analysis — See references/market-analysis-frameworks.md
For opportunity/idea research — See references/opportunity-assessment.md
Universal Synthesis Rules
- Lead with the answer — Start with the recommendation or key finding, then supporting evidence
- Quantify everything possible — Numbers > adjectives ("37% market growth" not "strong growth")
- Compare apples to apples — Normalize units, currencies, time periods
- Show trade-offs explicitly — Nothing is perfect; show what you gain and lose with each option
- Separate facts from opinions — Clearly mark data vs. interpretation
- Attribute sources — Every claim needs a source; every number needs a citation
- Include contrarian views — Note where experts disagree and why
Step 5: Deliver Results
Output Format Decision Tree
What did the user ask for?
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├─ "Best X for Y" → Ranked recommendation list with comparison table
├─ "Compare A vs B" → Head-to-head comparison matrix
├─ "Market data on X" → Data report with charts/tables
├─ "Ideas for X" → Scored opportunity list with viability assessment
├─ "How does X work?" → Structured explainer with sources
└─ General research → Executive summary + detailed findings
Every Research Output Must Include
- Executive summary (2-3 sentences answering the core question)
- Key findings (structured data — tables, ranked lists, or matrices)
- Methodology note (what was searched, how many sources, data vintage)
- Source list (URLs, publication names, dates)
- Caveats (limitations, data gaps, areas needing further research)
- Actionable next steps (what the user should do with this information)
Quality Standards
- No filler — Every sentence must add information value
- No hedging without reason — Be direct; qualify only when genuinely uncertain
- No generic advice — Tailor every finding to the user's specific constraints
- Current data — Flag anything older than 6 months; reject anything older than 2 years for fast-moving markets
- Honest gaps — If data doesn't exist or is unreliable, say so explicitly
Research Modes
Quick Research (respond within minutes)
- User needs a fast answer with reasonable confidence
- Check 3-5 top sources, provide ranked answer with brief rationale
- Mark as "quick research" — suggest deeper dive if needed
Deep Research (comprehensive analysis)
- User needs thorough, decision-grade intelligence
- Check 10-20+ sources, build comparison matrices, verify all claims
- Provide full structured report with methodology notes
Ongoing Research (iterative refinement)
- User refines criteria after seeing initial results
- Build on previous findings, narrow scope, add new dimensions
- Track what's been researched vs. what's new
Special Research Domains
Product Research (Electronics, Gadgets, Tools)
- Always include: price, key specs, user rating (aggregated), pros/cons
- Check for: recent model releases that may supersede recommendations
- Sources: manufacturer sites, Wirecutter, RTINGS, specialized review sites
- Watch for: regional availability, warranty differences, ecosystem lock-in
Financial Products (Credit Cards, Banks, Insurance)
- Always include: APR/fees, rewards structure, eligibility, fine print
- Check for: promotional rates vs. ongoing rates, hidden fees
- Sources: official issuer sites, NerdWallet, Bankrate, regulatory filings
- Watch for: affiliate bias in comparison sites, regional availability
Travel Research (Hotels, Flights, Destinations)
- Always include: price range, rating, location convenience, seasonal factors
- Check for: recent reviews (last 6 months), renovation status, hidden fees
- Sources: booking platforms, TripAdvisor, travel blogs, Google Maps reviews
- Watch for: fake reviews, seasonal pricing swings, currency fluctuations
Market & Industry Research
- Always include: market size, growth rate, key players, trends
- Check for: methodology behind market size estimates, sample sizes
- Sources: Statista, IBISWorld, industry associations, SEC filings, research papers
- Watch for: conflicting estimates between research firms, outdated projections
Business Ideas & Opportunities
- Always include: market gap, competition level, barrier to entry, revenue potential
- Check for: existing solutions, failure cases, regulatory requirements
- Sources: Crunchbase, Product Hunt, patent databases, startup databases
- Watch for: survivorship bias, overhyped markets, regulatory risks
Anti-Patterns (Never Do These)
- ❌ Present AI-generated data as real research (always use actual sources)
- ❌ Give a single recommendation without alternatives
- ❌ Ignore the user's specific constraints (budget, location, experience)
- ❌ Copy-paste from one source without cross-referencing
- ❌ Present outdated data without flagging it
- ❌ Skip source attribution
- ❌ Use vague language ("many experts say", "studies show") without specifics
- ❌ Over-research simple questions (match depth to complexity)
- ❌ Present sponsored/affiliate content as unbiased research
