AgentSkillsCN

research

为 cyber•Fund 的投资决策、内容创作以及个人项目,提供公司尽职调查、技术深度探究、市场分析与主题探索服务。支持三种强度级别(快速/标准/深度),以平衡速度与质量之间的权衡。

SKILL.md
--- frontmatter
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 TypeQuickStandardDeep
Company DDcompanycompany + market + financial+team +quality-reviewer
Technologytechtech + market+company +quality-reviewer
Marketmarketmarket + financial+company +quality-reviewer
Topic-Contentcontentcontent+quality-reviewer
Topic-Investmentinvestmentinvestment + 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:

code
~/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?")