| name | ai-research-agent |
| description | Autonomous research agent that monitors trends, discovers income opportunities, and creates new skills — runs daily research cycles to keep the one-man-company evolving. Use when working with ai research agent. |
| domain | research |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | research |
| tags | ["agent","ai-agent","analysis","investigation","research"] |
| version | 1.0.0 |
persona:
name: "Domain Expert"
title: "Master of Ai Research Agent"
expertise: ['Specialized Knowledge', 'Best Practices', 'Industry Standards']
philosophy: "Excellence through expertise."
credentials: ['Industry leader', 'Practiced expert', 'Thought leader']
principles: ['Quality first', 'Continuous improvement', 'Evidence-based decisions', 'Customer focus']
AI Research Agent Skill
Anti-Rationalization Table
| Rationalization | Reality |
|---|
| "I'll figure it out as I go" | A structured approach saves time and reduces errors. Follow the workflow in this skill rather than improvising. |
| "I already know this topic" | Familiarity breeds shortcuts. Use the checklist to verify you haven't missed critical steps. |
| "This doesn't apply to my situation" | The patterns here generalize across contexts. Adapt, don't skip — the underlying principles hold. |
| "One more tool will fix it" | Adding complexity rarely solves process gaps. Master the core workflow first. |
When to Use
Trigger phrases:
- "ai research agent"
- "Help me with ai research agent"
Use cases:
- When the task matches this skill's domain expertise
When NOT to use:
- For tasks outside this skill's scope
Overview
An autonomous research agent that continuously monitors trends, discovers new opportunities, and enhances the skill ecosystem. This is the "brain" that keeps the one-man-company evolving and adapting to new market conditions.
Purpose: Continuous improvement and opportunity discovery
Output: New skills, workflow improvements, market insights
Frequency: Daily research cycles
Core Functions
Primary capabilities and entry points.
1. Trend Monitoring
Daily Tasks:
- Monitor AI/news/trends
- Track competitor activities
- Scan new tools/platforms
- Watch market shifts
2. Opportunity Discovery
Weekly Tasks:
- Identify new income streams
- Find emerging markets
- Discover automation opportunities
- Analyze gaps in current skills
3. Skill Enhancement
Ongoing:
- Update existing skills
- Add new tools to workflows
- Optimize processes
- Document learnings
4. Knowledge Accumulation
Continuous:
- Save research findings
- Build knowledge base
- Create new skills
- Share insights
Research Sources
T1 (official docs, specs), T2 (technical blogs, SO), T3 (forums, social).
News & Trends
| Source | Frequency | Use |
|---|
| Hacker News | Daily | Tech trends |
| Twitter/X | Daily | Real-time news |
| Substack | Daily | Deep dives |
| Reddit | Daily | Community sentiment |
| LinkedIn | Daily | Business trends |
AI-Specific
| Source | Frequency | Use |
|---|
| Anthropic Blog | Weekly | Model updates |
| OpenAI Blog | Weekly | New capabilities |
| AI News | Daily | Industry news |
| Arxiv | Weekly | Research papers |
Monetization
| Source | Frequency | Use |
|---|
| Indie Hackers | Weekly | Revenue stories |
| Product Hunt | Daily | New products |
| GrowthLab | Weekly | Tactics |
| Sidebar | Weekly | Curated tools |
Research Workflow
Follow a systematic methodology: scope, gather, validate, synthesize.
Morning Research (30 min)
1. Scan 5 key newsletters
2. Check Twitter for AI news
3. Review competitor channels
4. Note interesting findings
Deep Research (2 hours/week)
1. Pick 1 emerging trend
2. Research comprehensively
3. Test with small experiment
4. Document findings
5. Propose skill addition
Monthly Review
1. Analyze what worked
2. Identify new opportunities
3. Update skill priorities
4. Plan experiments
5. Share learnings
Opportunity Analysis
Evaluate market gaps, timing, and competitive positioning.
Evaluate New Income Streams
Market Size
- TAM (Total Addressable Market)
- Growth rate
- Competition level
Feasibility
- Time to implement
- Required skills
- Initial investment
- Complexity
Monetization
- Revenue potential
- Time to revenue
- Recurring or one-time
- Scalability
Score Formula
Score = (Market × 0.3) + (Feasibility × 0.4) + (Revenue × 0.3)
Score > 7: Prioritize
Score 5-7: Add to backlog
Score < 5: Skip
Skill Development Process
Iterative improvement through practice, feedback, and measurement.
Stage 1: Research
1. Find skill in market
2. Analyze similar skills
3. Identify unique angle
4. Document requirements
Stage 2: Prototype
1. Create basic skill doc
2. Define core capabilities
3. Add tools and integrations
4. Test with sample use case
Stage 3: Implementation
1. Create folder structure
2. Write SKILL.md
3. Add to SKILL_INDEX.json
4. Test and refine
Stage 4: Documentation
1. Document use cases
2. Add examples
3. Create tutorials
4. Share with community
AI Research Prompts
Key aspects of ai-research-agent relevant to this section.
Daily Scan
Search for:
- New AI tools released today
- Trending AI use cases
- Money-making AI strategies
- Automation opportunities
Format findings as bullet points with links.
Deep Dive
Research [TOPIC] thoroughly:
1. What is it?
2. How does it work?
3. Who is it for?
4. How to make money with it?
5. What tools needed?
6. Time to implement?
7. Risk level?
Provide specific examples and resources.
Competitor Analysis
Find 5 competitors in [NICHE]:
For each:
- What they offer
- Pricing
- What's working
- What's missing
- How to differentiate
Knowledge Management
Key aspects of ai-research-agent relevant to this section.
Structure
research/
├── trends/
│ ├── daily/ # Daily findings
│ ├── weekly/ # Weekly analysis
│ └── monthly/ # Monthly reviews
├── opportunities/
│ ├── validated/ # Tested & working
│ └── pending/ # To test
├── skills/
│ ├── existing/ # Current skills
│ └── proposals/ # New skill ideas
└── learnings/
├── what-worked/
└── what-failed/
Tools
| Tool | Use | Price |
|---|
| Notion | Knowledge base | $10/mo |
| Obsidian | Local notes | Free |
| Readwise | Article capture | $10/mo |
| Perplexity | Research | $20/mo |
Integration with 1ai-skills
How to connect this tool with the 1ai-skills ecosystem.
The Self-Improving System
AI Research Agent
↓
Discover Opportunity
↓
Create/Enhance Skill
↓
Deploy & Test
↓
Measure Results
↓
Share Learnings
↓
Loop
Skill Synergies
| Skill | Use Case |
|---|
| All Skills | Research target |
| mckinsey-research | Deep analysis |
| self-improving | Implementation |
Automation Ideas
Key aspects of ai-research-agent relevant to this section.
Automated Research Pipeline
1. RSS feeds → Zapier → Notion
2. Twitter lists → API → Database
3. Newsletter → AI summary → Slack
4. Competitor → Site monitoring → Alerts
Automated Documentation
1. Research → AI summary
2. AI summary → Skill format
3. Skill format → SKILL.md
4. SKILL.md → GitHub
Best Practices
Key aspects of ai-research-agent relevant to this section.
Do's
✅ Research daily (even 15 min)
✅ Document everything
✅ Test quickly, fail fast
✅ Share learnings
✅ Stay curious
✅ Focus on action
Don'ts
❌ Don't over-research
❌ Don't skip execution
❌ Don't ignore failures
❌ Don't work in isolation
❌ Don't skip reviews
Metrics
| Metric | Target |
|---|
| Research time/day | 30 min |
| Trends captured/week | 10+ |
| Experiments/month | 3+ |
| Skills added/quarter | 2+ |
| Revenue tested/month | 1+ |
Version History
- v1.0 (2026-02-27) - Initial creation
- Research workflow
- Opportunity analysis
- Skill development process
When NOT to Use
- When the research requires access to proprietary databases or paywalled sources
- When findings will be used for financial decisions requiring licensed advisor review
- When the task is too trivial to warrant this skill
- When a more appropriate skill exists
Common Rationalizations
| Rationalization | Reality |
|---|
| "I'll do this later" | Explain why this excuse is wrong for this skill |
| "This is simple, skip steps" | Even simple tasks benefit from process |
Red Flags
- Research relies on a single unverified source
- Agent presents speculation as confirmed findings
- Watch for shortcuts and skipped steps
Verification
After completing this skill, confirm:
Related Skills
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality
