Deep Research Methodology: 8-Phase Pipeline

Overview

This document contains the detailed methodology for conducting deep research. The 8 phases represent a comprehensive approach to gathering, verifying, and synthesizing information from multiple sources.

Phase 1: SCOPE - Research Framing

Objective: Define research boundaries and success criteria

Activities:

1. Decompose the question into core components
2. Identify stakeholder perspectives
3. Define scope boundaries (what's in/out)
4. Establish success criteria
5. List key assumptions to validate

Ultrathink Application: Use extended reasoning to explore multiple framings of the question before committing to scope.

Output: Structured scope document with research boundaries

Phase 2: PLAN - Strategy Formulation

Objective: Create an intelligent research roadmap

Activities:

1. Identify primary and secondary sources
2. Map knowledge dependencies (what must be understood first)
3. Create search query strategy with variants
4. Plan triangulation approach
5. Estimate time/effort per phase
6. Define quality gates

Graph-of-Thoughts: Branch into multiple potential research paths, then converge on optimal strategy.

Output: Research plan with prioritized investigation paths

Phase 3: RETRIEVE - Parallel Information Gathering

Objective: Systematically collect information from multiple sources using parallel execution for maximum speed

CRITICAL: Execute ALL searches in parallel using a single message with multiple tool calls

Query Decomposition Strategy

Before launching searches, decompose the research question into 5-10 independent search angles:

1. Core topic (semantic search) - Meaning-based exploration of main concept
2. Technical details (keyword search) - Specific terms, APIs, implementations
3. Recent developments (date-filtered) - What's new in last 12-18 months (use current date from Step 0)
4. Academic sources (domain-specific) - Papers, research, formal analysis
5. Alternative perspectives (comparison) - Competing approaches, criticisms
6. Statistical/data sources - Quantitative evidence, metrics, benchmarks
7. Industry analysis - Commercial applications, market trends
8. Critical analysis/limitations - Known problems, failure modes, edge cases

Parallel Execution Protocol

Step 0: Get the current date

Before ANY searches, retrieve today's date using Bash: date +%Y-%m-%d Use the returned year for all date-filtered queries and recency checks. Do NOT assume a year from training data.

Step 1: Launch ALL searches concurrently (single message)

CRITICAL: Use correct tool and parameters to avoid errors

Primary: search-cli (multi-provider, always use first)

• Unified CLI aggregating Brave, Serper, Exa, Jina, and Firecrawl
• Auto-detects best provider per query type (academic, news, general, people)
• JSON output for structured processing: search "query" --json
• Modes: general, news, academic, scholar, patents, people, images, extract, scrape
• Example: search "quantum computing 2025" -m academic --json -c 15
• For page content extraction: search "URL" -m extract --json
• For scraping: search "URL" -m scrape --json
• Run via Bash tool: search "query" --json -c 10

Fallback: WebSearch (if search-cli fails or is unavailable)

• Built-in Claude web search, no setup required
• Parameters: query (required), optional allowed_domains, blocked_domains
• Use when: search-cli returns errors, rate-limited, or for domain-restricted queries

Optional: Exa MCP (if configured, for semantic/neural search)

• Tool name: mcp__Exa__exa_search
• Use for semantic exploration alongside search-cli keyword results

NEVER mix parameter styles - this causes "Invalid tool parameters" errors.

Step 2: Spawn parallel deep-dive agents

Use Task tool with general-purpose agents (3-5 agents) for:

• Academic paper analysis (PDFs, detailed extraction)
• Documentation deep dives (technical specs, API docs)
• Repository analysis (code examples, implementations)
• Specialized domain research (requires multi-step investigation)

Sub-agent output format: Require all sub-agents to return structured evidence, not free text:

{"claim": "specific claim text", "evidence_quote": "exact quote from source", "source_url": "https://...", "source_title": "...", "confidence": 0.85}

This prevents synthesis fatigue when merging results from 3-5 agents.

Evidence persistence (v3.0): After each retrieval batch, persist evidence immediately:

# Register the source first (returns stable source_id)
python scripts/citation_manager.py register-source --json '{"raw_url": "...", "title": "..."}' --dir [folder]

# Then persist each evidence span from that source
python scripts/evidence_store.py add --json '{"source_id": "...", "quote": "exact text", "evidence_type": "direct_quote", "locator": "page 5"}' --dir [folder]

Evidence must not live only in model context — it must be persisted to evidence.jsonl before synthesis begins. This ensures continuation agents and claim-support verification can access the full evidence trail.

Example parallel execution (using search-cli via Bash):

[Single message with multiple Bash tool calls]
- Bash: search "quantum computing 2026 state of the art" --json -c 10
- Bash: search "quantum computing limitations challenges" --json -c 10
- Bash: search "quantum computing commercial applications 2026" -m news --json -c 10
- Bash: search "quantum computing vs classical comparison" --json -c 10
- Bash: search "quantum error correction research" -m academic --json -c 10
- Task(subagent_type="general-purpose", description="Analyze quantum computing papers", prompt="Deep dive into quantum computing academic papers from [CURRENT_YEAR], extract key findings and methodologies")
- Task(subagent_type="general-purpose", description="Industry analysis", prompt="Analyze quantum computing industry reports and market data, identify commercial applications")
- Task(subagent_type="general-purpose", description="Technical challenges", prompt="Extract technical limitations and challenges from quantum computing research")

Example parallel execution (using Exa MCP - if available):

[Single message with multiple tool calls]
- mcp__Exa__exa_search(query="quantum computing state of the art", type="neural", num_results=10, start_published_date="[use current year from Step 0]")
- mcp__Exa__exa_search(query="quantum computing limitations", type="keyword", num_results=10)
- mcp__Exa__exa_search(query="quantum computing commercial", type="auto", num_results=10, start_published_date="[use current year from Step 0]")
- mcp__Exa__exa_search(query="quantum error correction", type="neural", num_results=10, include_domains=["arxiv.org"])
- Task(subagent_type="general-purpose", description="Academic analysis", prompt="Analyze quantum computing academic papers")

Step 3: Collect and organize results

As results arrive:

1. Extract key passages with source metadata (title, URL, date, credibility)
2. Track information gaps that emerge
3. Follow promising tangents with additional targeted searches
4. Maintain source diversity (mix academic, industry, news, technical docs)
5. Monitor for quality threshold (see FFS pattern below)

First Finish Search (FFS) Pattern

Adaptive completion based on quality threshold:

Quality gate: Proceed to Phase 4 when FIRST threshold reached:

• Quick mode: 10+ sources with avg credibility >60/100 OR 2 minutes elapsed
• Standard mode: 15+ sources with avg credibility >60/100 OR 5 minutes elapsed
• Deep mode: 25+ sources with avg credibility >70/100 OR 10 minutes elapsed
• UltraDeep mode: 30+ sources with avg credibility >75/100 OR 15 minutes elapsed

Continue background searches:

• If threshold reached early, continue remaining parallel searches in background
• Additional sources used in Phase 5 (SYNTHESIZE) for depth and diversity
• Allows fast progression without sacrificing thoroughness

Quality Standards

Source diversity requirements:

• Minimum 3 source types (academic, industry, news, technical docs)
• Temporal diversity (mix of recent 12-18 months + foundational older sources)
• Perspective diversity (proponents + critics + neutral analysis)
• Geographic diversity (not just US sources)

Credibility tracking:

• Score each source 0-100 using source_evaluator.py
• Flag low-credibility sources (<40) for additional verification
• Prioritize high-credibility sources (>80) for core claims

Techniques:

• Use search-cli for all searches (primary tool, multi-provider)
• Fall back to WebSearch if search-cli fails or is rate-limited
• Use WebFetch for deep dives into specific sources (secondary)
• Use Exa search (via WebSearch with type="neural") for semantic exploration
• Use Grep/Read for local documentation
• Execute code for computational analysis (when needed)
• Use Task tool to spawn parallel retrieval agents (3-5 agents)

Output: Organized information repository with source tracking, credibility scores, and coverage map

Phase 4: TRIANGULATE - Cross-Reference Verification

Objective: Validate information across multiple independent sources

Activities:

1. Identify claims requiring verification
2. Cross-reference facts across 3+ sources
3. Flag contradictions or uncertainties
4. Assess source credibility
5. Note consensus vs. debate areas
6. Document verification status per claim

Quality Standards:

• Core claims must have 3+ independent sources
• Flag any single-source information
• Note recency of information
• Identify potential biases

Output: Verified fact base with confidence levels

Phase 4.5: OUTLINE REFINEMENT - Dynamic Evolution (WebWeaver 2025)

Objective: Adapt research direction based on evidence discovered

Problem Solved: Prevents "locked-in" research when evidence points to different conclusions or uncovers more important angles than initially planned.

When to Execute:

• Standard/Deep/UltraDeep modes only (Quick mode skips this)
• After Phase 4 (TRIANGULATE) completes
• Before Phase 5 (SYNTHESIZE)

Activities:

1. Review Initial Scope vs. Actual Findings

• Compare Phase 1 scope with Phase 3-4 discoveries
• Identify unexpected patterns or contradictions
• Note underexplored angles that emerged as critical
• Flag overexplored areas that proved less important

1. Evaluate Outline Adaptation Need

Signals for adaptation (ANY triggers refinement):

• Major findings contradict initial assumptions
• Evidence reveals more important angle than originally scoped
• Critical subtopic emerged that wasn't in original plan
• Original research question was too broad/narrow based on evidence
• Sources consistently discuss aspects not in initial outline

Signals to keep current outline:

• Evidence aligns with initial scope
• All key angles adequately covered
• No major gaps or surprises

1. Refine Outline (if needed)

Update structure to reflect evidence:

• Add sections for unexpected but important findings
• Demote/remove sections with insufficient evidence
• Reorder sections based on evidence strength and importance
• Adjust scope boundaries based on what's actually discoverable

Example adaptation:

   Original outline:
   1. Introduction
   2. Technical Architecture
   3. Performance Benchmarks
   4. Conclusion

   Refined after Phase 4 (evidence revealed security as critical):
   1. Introduction
   2. Technical Architecture
   3. **Security Vulnerabilities (NEW - major finding)**
   4. Performance Benchmarks (demoted - less critical than expected)
   5. **Real-World Failure Modes (NEW - pattern emerged)**
   6. Synthesis & Recommendations

1. Targeted Gap Filling (if major gaps found)

If outline refinement reveals critical knowledge gaps:

• Launch 2-3 targeted searches for newly identified angles
• Quick retrieval only (don't restart full Phase 3)
• Time-box to 2-5 minutes
• Update triangulation for new evidence only

1. Document Adaptation Rationale

Record in methodology appendix:

• What changed in outline
• Why it changed (evidence-driven reasons)
• What additional research was conducted (if any)

Quality Standards:

• Adaptation must be evidence-driven (cite specific sources that prompted change)
• No more than 50% outline restructuring (if more needed, scope was severely mis scoped)
• Retain original research question core (don't drift into different topic entirely)
• New sections must have supporting evidence already gathered

Output: Refined outline that accurately reflects evidence landscape, ready for synthesis

Anti-Pattern Warning:

• ❌ DON'T adapt outline based on speculation or "what would be interesting"
• ❌ DON'T add sections without supporting evidence already in hand
• ❌ DON'T completely abandon original research question
• ✅ DO adapt when evidence clearly indicates better structure
• ✅ DO document rationale for changes
• ✅ DO stay within original topic scope

Phase 5: SYNTHESIZE - Deep Analysis

Objective: Connect insights and generate novel understanding

Activities:

1. Identify patterns across sources
2. Map relationships between concepts
3. Generate insights beyond source material
4. Create conceptual frameworks
5. Build argument structures
6. Develop evidence hierarchies

Ultrathink Integration: Use extended reasoning to explore non-obvious connections and second-order implications.

Output: Synthesized understanding with insight generation

Phase 6: CRITIQUE - Quality Assurance

Objective: Rigorously evaluate research quality

Activities:

1. Review for logical consistency
2. Check citation completeness
3. Identify gaps or weaknesses
4. Assess balance and objectivity
5. Verify claims against sources
6. Test alternative interpretations

Red Team Questions:

• What's missing?
• What could be wrong?
• What alternative explanations exist?
• What biases might be present?
• What counterfactuals should be considered?

Persona-Based Critique (Deep/UltraDeep only): Simulate 2-3 specific critic personas relevant to the topic:

• "Skeptical Practitioner" — Would someone doing this daily trust these findings?
• "Adversarial Reviewer" — What would a peer reviewer reject?
• "Implementation Engineer" — Can these recommendations actually be executed?

Critical Gap Loop-Back: If critique identifies a critical knowledge gap (not just a writing issue), return to Phase 3 with targeted "delta-queries" before proceeding to Phase 7. Time-box to 3-5 minutes. This prevents publishing reports with known blind spots.

Output: Critique report with improvement recommendations

Phase 7: REFINE - Iterative Improvement

Objective: Address gaps and strengthen weak areas

Activities:

1. Conduct additional research for gaps
2. Strengthen weak arguments
3. Add missing perspectives
4. Resolve contradictions
5. Enhance clarity
6. Verify revised content

Output: Strengthened research with addressed deficiencies

Phase 8: PACKAGE - Report Generation

Objective: Deliver professional, actionable research

Activities:

1. Structure report with clear hierarchy
2. Write executive summary
3. Develop detailed sections
4. Create visualizations (tables, diagrams)
5. Compile full bibliography
6. Add methodology appendix

Output: Complete research report ready for use

Advanced Features

Graph-of-Thoughts Reasoning

Rather than linear thinking, branch into multiple reasoning paths:

• Explore alternative framings in parallel
• Pursue tangential leads that might be relevant
• Merge insights from different branches
• Backtrack and revise as new information emerges

Parallel Agent Deployment

Use Task tool to spawn sub-agents for:

• Parallel source retrieval
• Independent verification paths
• Competing hypothesis evaluation
• Specialized domain analysis

Adaptive Depth Control

Automatically adjust research depth based on:

• Information complexity
• Source availability
• Time constraints
• Confidence levels

Citation Intelligence

Smart citation management:

• Track provenance of every claim
• Link to original sources
• Assess source credibility
• Handle conflicting sources
• Generate proper bibliographies