Deep Research Swarm

Deep Research

Orchestrate multi-agent epistemic triangulation: diverge across research dimensions, detect overlaps and contradictions, verify deeply, then converge into a validated synthesis. Swarm parallelism serves epistemic robustness — not merely speed.

Adaptive routing ensures the pipeline fits the task: wide-search topics get a two-stage parallel swarm (breadth then depth); file-based tasks skip or augment external search; focused queries go straight to dimension decomposition.

Output Directory — MANDATORY

All deep research output files MUST be saved under:

/mnt/agents/output/research/

This is non-negotiable. Every file produced in any phase MUST use this directory as the base path. Do NOT save any research artifact to /mnt/agents/output/ directly — always use the /mnt/agents/output/research/ subdirectory.

Before writing any file, ensure the directory exists (create it if not).

Workflow Overview

User Query
  │
  ▼
Phase 0: Intent & Input Router
  │
  ├─ Route A: Wide Search (broad/exploratory, no clear dimensions)
  │   → Phase 1 (Quick Landscape)
  │     → Phase 1W (Multi-Agent Wide Exploration) ★ NEW
  │       → Phase 2 (Decompose, informed by rich landscape)
  │         → Phase 3 (Parallel Deep Dive)
  │           → Phase 4 (Cross-Verify) → Phase 5 (if conflicts)
  │             → Phase 6 (Insight Extraction) → Phase 7 (Report via writing skill)
  │
  ├─ Route B: Focused Search (specific question, clear dimensions)
  │   → Phase 1 (Landscape) → Phase 2 (Decompose)
  │     → Phase 3 (Parallel Deep Dive) → Phase 4 (Cross-Verify)
  │       → Phase 5 (if conflicts) → Phase 6 (Insight Extraction) → Phase 7 (Report)
  │
  ├─ Route C: File-Only Research (user explicitly restricts to file content)
  │   → Phase F (File Intake & Deep Analysis) ★ NEW
  │     → Phase 2 (Decompose from file themes)
  │       → Phase 3-F (Multi-Agent File Deep Dive, NO external search)
  │         → Phase 4 (Cross-Verify across file analyses)
  │           → Phase 6 (Insight Extraction) → Phase 7 (Report via writing skill)
  │
  └─ Route D: File-Augmented Research (files as primary reference + external supplement)
      → Phase F (File Intake & Deep Analysis) ★ NEW
        → Phase 1 (Targeted Landscape, informed by file gaps)
          → Phase 2 (Decompose, merging file themes + external landscape)
            → Phase 3 (Parallel Deep Dive, each agent has file context + search)
              → Phase 4 (Cross-Verify) → Phase 5 (if conflicts)
                → Phase 6 (Insight Extraction) → Phase 7 (Report via writing skill)

Phase 0: Intent & Input Router

Goal: Classify the user's request into the correct route before any research begins.

Process:

1. Check for uploaded files:

   • Files present + explicit "only based on files" language → Route C
   • Files present + no restriction / "refer to" / "combine with" / "help me complete" → Route D
   • No files → continue to step 2

2. Assess topic breadth:

   • Broad, open-ended, landscape-level query (e.g., "current state of XX industry", "research XX field for me", "XX vs YY vs ZZ comprehensive comparison") → Route A
   • Specific, bounded question with identifiable dimensions → Route B

3. When ambiguous, default to:

   • Route A if the topic is clearly multi-faceted and no clear angle is given
   • Route D over Route C if file intent is unclear (prefer richer output)

Output: State the selected route and rationale in one sentence, then proceed to the first phase of that route.

Classification signals summary:

Epistemic Reset Rule

Before any analysis or narrative generation, the system MUST:

• Assume internal knowledge may be outdated or incomplete. Always retrieve the current date and time using bash tool before any analysis or external search.
• Using bash to check the time now.
• Time-awareness: When the user's query has time-sensitivity requirements (e.g., "2026 Q1", "recent 6 months", "latest", "current"), treat the specified or implied time range as a hard constraint — search queries must target that window, and findings outside it should be flagged.
• Perform external wide search to establish the evidence landscape (except Route C)
• Avoid generating any factual claims before search/file-analysis outputs
• Search language rule: All search queries MUST be in the same language as the user's message. If the user writes in Chinese, search in Chinese; if in English, search in English. This ensures results are relevant to the user's locale and context.
• All outputs MUST use inline citations [^number^] referencing original sources.

Phase F: File Intake & Deep Analysis (Route C & D Only)

Goal: Extract structured knowledge from all uploaded files, build an evidence map, and identify themes, claims, contradictions, and gaps across the file corpus.

Trigger: Route C or Route D (any request with user-uploaded files).

Process:

1. File Inventory: List all uploaded files with type, size, and a one-line content summary.

2. Per-File Extraction — for each file, extract:

   • Core themes and topics
   • Key claims, arguments, and conclusions
   • Data points, statistics, and figures (with page/section references)
   • Methodology (if applicable)
   • Limitations, caveats, or biases noted by the author

3. Cross-File Mapping:

   • Identify overlapping themes across files
   • Detect contradictions or conflicting data between files
   • Map complementary information (File A provides context that File B lacks)
   • Identify gaps — important aspects of the topic that no file covers

4. Theme Consolidation: Produce a consolidated theme list that will feed into Phase 2 dimension decomposition.

Route-specific behavior:

• Route C: The gap analysis is informational only (noted in output, but no external search will fill gaps). The consolidated themes become the sole basis for Phase 2.
• Route D: The gap analysis directly informs Phase 1's search strategy — Phase 1 targets these gaps with external search.

Output: Save to /mnt/agents/output/research/{topic}_file_analysis.md containing:

• File inventory table
• Per-file extraction summaries
• Cross-file mapping (overlaps, contradictions, complementarities)
• Gap analysis
• Consolidated theme list

Phase 1: Landscape Scan (Route A, B, D)

Goal: Establish an evidence-grounded global narrative landscape through coarse-to-fine exploration before committing to dimension decomposition.

This phase operates under External-Evidence-First Mode. No analytical narrative may be generated before search outputs are reviewed. Every key finding must include [^number^] citation inline.

Route-specific behavior:

• Route A (Wide Search): Lighter scan — 3–5 searches for macro framing only. The heavy lifting is delegated to Phase 1W.
• Route B (Focused): Full 5-search coarse-to-fine scan as below.
• Route D (File-Augmented): Targeted scan — use file gap analysis from Phase F to guide search queries. Focus on areas the files don't cover. 3–5 searches.

Process (full version for Route B; Route A/D adapt per above):

1. Perform 5 broad exploratory searches by yourself. Search MUST follow a coarse-to-fine progression. Don't search details at beginning.
   • Level 1 – Macro Overview (Search 1-2): Broad overview queries, Industry reports, High-level statistics, Wikipedia-level but verified via authoritative sources, General summaries
   • Level 2 – Structural Mapping (Search 2-4): Market structure, Major actors, Regulatory bodies
   • Level 3 – Emerging Issues & Tensions (Search 5): Recent developments, Conflicting narratives, Trend signals
2. After EACH search, output:
   • Key findings (concise)
   • Dominant narratives identified
   • Controversies or conflicting claims detected
   • Key actors and authoritative sources discovered
   • Gaps requiring deeper investigation
3. Revise dimension decomposition if landscape reveals unexpected structure

Phase 1W: Multi-Agent Wide Exploration (Route A Only)

Goal: Maximize search breadth through parallel sub-agent exploration before committing to dimensions. This is the key differentiator for wide-search scenarios — the orchestrator cannot achieve sufficient breadth alone.

Trigger: Route A only. Executes after Phase 1 (Quick Landscape).

Process:

1. Based on Phase 1's macro framing, identify 5–8 broad exploration facets. Facets should be:

   • Mutually complementary (together they cover the full problem space)
   • Partially overlapping (≥20% overlap for cross-verification)
   • Examples of facet types: technology landscape, market/commercial landscape, regulatory/policy landscape, competitive dynamics, user/consumer perspective, supply chain, geographic variations, historical evolution, emerging disruptions

2. Deploy ≥5 sub-agents in parallel, one per facet. Each sub-agent's prompt MUST include:

   • (1) Facet scope: what broad area to explore, with explicit boundaries
   • (2) Phase 1 context: key findings from the quick landscape scan
   • (3) Search requirements: ≥10 independent searches per agent, coarse-to-fine within the facet
   • (4) Output format: structured findings (see below)
   • (5) Output file path: /mnt/agents/output/research/{topic}_wide{NN}.md

3. Each wide-exploration sub-agent MUST:

   • Perform ≥10 independent searches with varied queries (no keyword recycling)
   • Cast a wide net: different source types, different angles within the facet
   • Identify key players, data points, trends, and controversies within their facet
   • Flag areas that warrant deep investigation in Phase 3
   • Save output to /mnt/agents/output/research/{topic}_wide{NN}.md

Sub-Agent Output Format (all citations use [^number^]):

## Facet: [facet name]

### Key Findings
- [finding with inline citation]

### Major Players & Sources
- [entity]: [role/relevance]

### Trends & Signals
- [trend with citation]

### Controversies & Conflicting Claims
- [conflict description with citations to both sides]

### Recommended Deep-Dive Areas
- [area]: [why it warrants depth]

4. Orchestrator Synthesis: After all wide-exploration agents complete:
   • Read all {topic}_wide{NN}.md files
   • Merge findings into a unified landscape map
   • Identify the most promising and contentious areas
   • Feed this rich landscape into Phase 2 for dimension decomposition

Output: Each sub-agent saves to /mnt/agents/output/research/{topic}_wide{NN}.md. Orchestrator uses these to inform Phase 2.

Key principle: Phase 1W is about breadth — finding what exists, who matters, what's happening. Phase 3 is about depth — investigating each dimension thoroughly. The two-stage swarm ensures nothing important is missed.

Phase 2: Dimension Decomposition

Goal: Finalize research dimensions and prepare sub-agent assignments.

Input varies by route:

• Route A: Phase 1 + Phase 1W wide exploration outputs (richest input)
• Route B: Phase 1 landscape scan
• Route C: Phase F file analysis — consolidated theme list only (no external input)
• Route D: Phase F file analysis + Phase 1 targeted landscape scan

Rules:

• ≥10 dimensions (mandatory minimum). More is better — 10–20 dimensions depending on topic complexity
• Each dimension approaches the topic from a distinct angle or scenario, ensuring the research covers the problem space from fundamentally different perspectives
• Dimensions may be organized by:
  • Analytical angle (technical, economic, regulatory, ethical, competitive, user-facing, supply-chain, etc.)
  • Scenario (optimistic, pessimistic, status quo, disruption, black swan, etc.)
  • Stakeholder viewpoint (consumer, enterprise, regulator, investor, competitor, workforce, etc.)
  • Geography or market segment (China, US, EU, emerging markets, etc.)
  • Time horizon (historical origins, current state, 1-year outlook, 5-year outlook, etc.)
  • File-derived theme (Route C/D: dimensions can map to major themes identified in Phase F)
  • Or any combination — the goal is maximum coverage with deliberate partial overlap
• ≥30% conceptual overlap between related dimensions — overlap creates cross-verification pressure
• Each dimension MUST cover:
  1. Current state — what is happening now from this angle, always with inline [^number^] citations
  2. Key evidence — data, sources, and concrete examples using [^number^]
  3. Tensions and counter-arguments — what opposing views exist from this angle, all claims referenced via [^number^]

Route C special rule: For file-only research, dimensions are derived entirely from file themes. Each dimension should map to one or more files, and the scope should reference specific file sections.

Output: a numbered dimension list (≥10 items) with clear scope, assigned angle/scenario, and expected source types for each.

Phase 3: Parallel Deep Dive (Sub-Agent Deployment)

Goal: Execute depth-first research across all dimensions in parallel. ≥10 sub-agents launched simultaneously, one per dimension.

Route-specific variants:

Standard Mode (Route A, B, D)

1. Create one sub-agent per dimension via task — launch all sub-agents in parallel (do not serialize)
2. Each sub-agent investigates from its assigned angle/scenario, producing findings that are distinct from but partially overlapping with other agents
3. Each sub-agent's prompt MUST include:
   • (1) Mission: the dimension's scope, four required angles (current state, history, stakeholders, counter-narrative), and depth expectations
   • (2) Context: key findings from earlier phases relevant to this dimension
   • (3) File context (Route D only): relevant excerpts from Phase F file analysis — the sub-agent should treat file content as primary evidence and search for supplementary/corroborating external sources
   • (4) Output format: the evidence template below
   • (5) Output file path: the sub-agent MUST save to /mnt/agents/output/research/{topic}_dim{NN}.md

Sub-Agent Requirements (Standard Mode):

• Perform ≥20 independent searches (no repeated keyword cycles)
• Investigate primary sources where possible (government sites, academic journals, official filings, major media)
• Trace claims back to original publication
• Identify and document counter-arguments
• Avoid content farms, anonymous blogs, SEO aggregators
• Route D: Explicitly reference and build upon file-derived evidence. Search externally to fill gaps, verify file claims, and add depth. Clearly distinguish file-sourced vs. search-sourced evidence.
• Save output to /mnt/agents/output/research/{topic}_dim{NN}.md

File-Only Mode (Route C)

1. Create one sub-agent per dimension via task — launch all sub-agents in parallel
2. Each sub-agent analyzes its assigned dimension using only the uploaded file content — NO external search
3. Each sub-agent's prompt MUST include:
   • (1) Mission: the dimension's scope and the specific files/sections relevant to it
   • (2) Full file content or relevant excerpts: provide the actual file content the agent needs (do not assume the sub-agent can access files independently)
   • (3) Analysis requirements: cross-reference between files, identify patterns, evaluate strength of evidence, note limitations
   • (4) Output format: the evidence template below (adapted — Source field references file name + section instead of URL)
   • (5) Output file path: /mnt/agents/output/research/{topic}_dim{NN}.md

Sub-Agent Requirements (File-Only Mode):

• Thoroughly analyze all provided file content relevant to the dimension
• Cross-reference claims and data across multiple files
• Evaluate evidence quality and identify potential biases
• Note where file evidence is thin or contradictory
• Identify implicit assumptions in the source material
• Do NOT perform any external search
• Save output to /mnt/agents/output/research/{topic}_dim{NN}.md

Sub-Agent Output Format (all modes)

All citations use [^number^]:

Claim: [identified claim with inline citation]
Source: [source name / file name]
URL: [source URL / "File: {filename}, Section: {section}"]
Date: [publication date / "N/A" for files]
Excerpt: [verbatim raw excerpt — no paraphrasing]
Context: [surrounding context]
Confidence: [high / medium / low]

Output: Each sub-agent saves its output to /mnt/agents/output/research/{topic}_dim{NN}.md.

Phase 4: Cross-Verification Engine (Orchestrator)

Goal: Compare all dimension outputs, classify confidence, surface contradictions, and save the verification results to a file for downstream use by report-writing.

Process:

1. Read all /mnt/agents/output/research/{topic}_dim{NN}.md files
2. Categorize every finding into one of four tiers:

3. List all Conflict Zone items explicitly — contradictions are highlighted and analyzed, never suppressed. Temporal conflicts are Conflict Zone: if agents report data from different time periods for the same metric, flag this as a temporal inconsistency and record which time period each data point belongs to.
4. Determine if Phase 5 is needed (any Conflict Zone or critical Low Confidence items)
   • Route C exception: Phase 5 is skipped (no external search allowed). Conflicts are documented as-is and carried into Phase 6.
5. Inline citations [^number^] must be preserved
6. Conflict Zone analysis must include [^number^] references to all sources involved

Output: Save the complete cross-verification results (all tiers + conflict zone analysis) to /mnt/agents/output/research/{topic}_cross_verification.md. This file is critical — it carries confidence classifications that guide report-writing.

Phase 5: Targeted Validation (Conditional)

Goal: Resolve conflicts and strengthen weak findings.

Trigger: Execute only if Phase 4 identified Conflict Zone or critical Low Confidence items. NOT available for Route C (file-only research cannot invoke external search).

All validation outputs must preserve inline [^number^] citations.

Process:

1. For each unresolved item, deploy a focused sub-agent with:

   • The specific conflicting claims and their sources
   • Instructions to find independent evidence that resolves the disagreement
   • Minimum 3 additional searches per conflict

2. Repeat until each item is either:

   • Resolved — reclassified to High/Medium Confidence with new evidence
   • Explicitly marked unresolved — documented as a genuine disagreement in the field

3. Update /mnt/agents/output/research/{topic}_cross_verification.md with the resolution results.

Phase 6: Insight Extraction

Goal: Identify non-obvious insights that do not explicitly appear in previous findings, but emerge from cross-dimension analysis.

Definition of Insight: An insight is a higher-level inference derived from multiple validated findings. It must not repeat previously stated claims or evidence.

Process:

1. Review all validated findings from Phase 3–5 (and Phase F file analysis, if applicable).
2. Identify patterns that only become visible when comparing multiple dimensions.
3. Extract insights that reveal: structural relationships, hidden tensions, emerging trends, systemic risks, strategic opportunities.
4. Ensure each insight is supported indirectly by evidence from at least two dimensions.

Route-specific emphasis:

• Route C/D (file-based): Prioritize insights that emerge from cross-file synthesis — patterns that no single file reveals on its own. For Route D, also highlight where external evidence strengthens, contradicts, or extends file-derived conclusions.
• Route A (wide search): Prioritize insights that bridge different exploration facets — connections between areas that were explored independently.

Genre-aware insight extraction: Adjust emphasis based on the intended downstream writing format:

• Report (industry report, market analysis, consulting deliverable): prioritize actionable strategic insights, market opportunities, competitive dynamics, and forward-looking implications
• Academic paper (survey, empirical study, literature review): prioritize research gaps, methodological contradictions, theoretical tensions, and novel contribution angles that position against prior work
• When the target genre is unclear, produce insights in a neutral format covering both strategic and academic angles — the writing skill will adapt

Output Requirements:

For each insight, record:

• Insight: concise statement of the inferred pattern
• Derived From:
  • Dimension references (e.g., Dim 02, Dim 07)
  • Supporting evidence clusters (include file references for Route C/D)
• Rationale: explanation of how the insight emerges from the evidence
• Implications: potential impact or significance
• Confidence: high / medium / exploratory

Output: Save all insights to /mnt/agents/output/research/{topic}_insight.md. This file is the core synthesis of the entire deep research process and will be the primary input for the downstream writing skill.

Rules:

• Insights must not duplicate existing findings.
• Insights must be derived from cross-dimension comparison.
• Avoid speculative claims unsupported by evidence.
• Minimum output: 5 insights.
• Insights must include references to supporting evidence using inline citations [^number^]

Phase 7: Handoff to Writing Skill

Goal: Hand off all research artifacts to the appropriate writing skill for final document generation.

After cross-verification (and optional targeted validation) and insight extraction are complete:

1. Verify all required files exist under /mnt/agents/output/research/:
   • {topic}_dim{NN}.md — all dimension files (≥10)
   • {topic}_cross_verification.md — confidence tiers and conflict analysis
   • {topic}_insight.md — cross-dimension insights
   • {topic}_file_analysis.md — (Route C/D only) file intake analysis
   • {topic}_wide{NN}.md — (Route A only) wide exploration outputs
2. Determine the target writing skill based on user intent:
   • report-writing — industry reports, market analysis, consulting deliverables, policy briefs
   • paper-writing — academic papers, survey papers, literature reviews, conference submissions
3. Invoke the selected writing skill, providing explicit file paths in the handoff:
   • Insight file: /mnt/agents/output/research/{topic}_insight.md
   • Cross-verification file: /mnt/agents/output/research/{topic}_cross_verification.md
   • Dimension files: /mnt/agents/output/research/{topic}_dim01.md through {topic}_dim{NN}.md
   • File analysis (Route C/D): /mnt/agents/output/research/{topic}_file_analysis.md
   • Wide exploration files (Route A): /mnt/agents/output/research/{topic}_wide{NN}.md
   • Research directory: /mnt/agents/output/research/
4. The orchestrator MUST explicitly tell the writing skill that deep research is complete and no additional research sub-agents are needed.
5. The final document MUST incorporate insights from Phase 6.
6. If the user specified a time range, the orchestrator MUST verify that key data points and dates in the final artifacts fall within that range before handoff.

Output Rules

• Insights from Phase 6 must be incorporated into the final document — as a dedicated Insights section (for reports) or woven into Discussion/Contribution sections (for papers).
• Insights must not be omitted even if the user requested a shorter output format.
• All outputs must include [^number^] style citations.
• The final document must clearly distinguish verified findings, conflict zones, and derived insights.
• Route C: Citations reference file names and sections (not URLs). The report must clearly state it is based solely on the provided files.
• Route D: Citations must distinguish file-sourced evidence from externally-sourced evidence.
• If the user doesn't specify file type, default to Word format.

Core Principles

1. Depth over breadth (Route B) / Breadth then depth (Route A). Shallow aggregation is forbidden. Each dimension must be investigated thoroughly before moving on.
2. Raw evidence required. Sub-agents must return verbatim excerpts with source URLs/file references and dates. No paraphrased-only outputs.
3. Contradictions are signal. Conflicts are highlighted and analyzed, never suppressed or averaged away.
4. Everything is a file. Never output long-form research content in chat. Chat is for status updates only.
5. Source quality matters. Prioritize: government sites, academic journals, official filings, major media. Avoid: content farms, anonymous blogs, SEO aggregators. For file-based routes, treat user-provided files as primary authoritative sources.
6. Search budget by route:
   • Route A: ≥5 wide agents × ≥10 searches + ≥10 deep agents × ≥20 searches = ≥250 total searches
   • Route B: ≥10 agents × ≥20 searches = ≥200 total searches
   • Route C: 0 external searches (file-only)
   • Route D: ≥10 agents × ≥15 searches = ≥150 total searches (reduced because files provide base evidence)
7. All outputs must include [^number^] style citations.
8. All files under /mnt/agents/output/research/. No exceptions.
9. Route C respects user intent. If the user says "only based on files", do NOT sneak in external searches. Fidelity to user intent is paramount.
10. Route D balances sources. File content is primary; external search fills gaps and adds depth. Do not let external sources overshadow the user's provided materials.

File Naming

All files are saved under /mnt/agents/output/research/.