How do I install the Research skill?

Run npx skillmds add majiayu000/research-7 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Research safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Research?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Research free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Research?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Research by majiayu000 — Agent Skill

Name: Research
Rating: 4.666666666666667 (3 reviews)
Author: majiayu000

Research

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.

majiayu000 e99d7ea 2 files · 4.5 KB Updated Sep 9, 2026 567 repo stars

File contents

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?")

---name: research-7description: 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?")

Frequently asked questions