research

name	research
description	Company due diligence, technology deep-dives, market analysis, and topic exploration for cyber•Fund investment decisions, content creation, and personal projects. Supports 3 intensity levels (quick/standard/deep) for speed-quality tradeoffs.

Research Skill

Company due diligence, technology deep-dives, market analysis, and topic exploration for cyber•Fund investment decisions, content creation, and personal projects.

Capabilities

• Company Research: Comprehensive DD on target companies
• Technology Research: Deep technical analysis of technologies
• Market Research: Market sizing, dynamics, and opportunity assessment
• Topic Research (Content): Ideas, narratives, people for essays/tweets
• Topic Research (Investment): Market dynamics and opportunities for investment thesis

Research Intensity Levels

• 🔍 Quick (10-30s): 1 agent
• 🔬 Standard (2-5m): 2-3 agents [DEFAULT]
• 🔎 Deep (5-15m): 3-5 agents + quality-reviewer

See shared/intensity-tiers.md for full specification.

Workflow

All research types use one universal workflow:

• workflows/orchestrator.md

The orchestrator dynamically selects agents based on research type and intensity.

Agent Selection

See shared/agent-selection-matrix.md for full matrix.

Research Type	Quick	Standard	Deep
Company DD	company	company + market + financial	+team +quality-reviewer
Technology	tech	tech + market	+company +quality-reviewer
Market	market	market + financial	+company +quality-reviewer
Topic-Content	content	content	+quality-reviewer
Topic-Investment	investment	investment + market	+financial +quality-reviewer

Agents

Research agents (autonomous MCP access):

• company-researcher: Business model, product, traction
• market-researcher: TAM, dynamics, trends
• financial-researcher: Funding, metrics, comparables
• team-researcher: Founder backgrounds, team assessment
• tech-researcher: Technology deep-dives
• content-researcher: Academic papers, social media, first-principles (for content)
• investment-researcher: Market dynamics, opportunities, timing (for investment)

Quality & Synthesis:

• quality-reviewer: Gap analysis, contradiction detection (deep only, max 1 iteration)
• synthesizer: Consolidate parallel research outputs

Common References

• shared/agent-selection-matrix.md - Dynamic agent selection
• shared/investment-lens.md - cyber•Fund investment philosophy
• shared/mcp-strategy.md - MCP tool selection
• shared/output-standards.md - Formats and emoji conventions
• shared/intensity-tiers.md - 3-tier intensity spec

Output Locations

All research creates timestamped workspace:

~/CybosVault/private/deals/<company>~/CybosVault/private/research/MMDD-<slug>-YY/   # Company
~/CybosVault/private/research/<topic>/MMDD-<slug>-YY/           # Tech/Market/Topic
├── raw/                                     # Agent outputs
└── report.md                                # Final synthesis

Key Principles

1. Agents do ALL data gathering - Main session orchestrates, agents make MCP calls
2. No redundancy - Each agent makes its own calls autonomously
3. Dynamic selection - Agents chosen based on research type + intensity
4. Quality loop - Deep mode includes quality-reviewer (max 1 iteration)

Investment Context

All research applies cyber•Fund's investment philosophy:

• Path to $1B+ revenue (not niche $50M ARR outcomes)
• Defensible moat (data, network effects, hard tech)
• Clear business model (revenue > token speculation)
• Strong founders (high energy, sales DNA, deep expertise)
• Market timing ("why now?")