| 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
- Agents do ALL data gathering - Main session orchestrates, agents make MCP calls
- No redundancy - Each agent makes its own calls autonomously
- Dynamic selection - Agents chosen based on research type + intensity
- 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?")