Research Automation

Automated research system that searches the web for new developments in peptides, biohacking, longevity, and trending health topics.

What It Does

• Web Search: Queries multiple sources for latest research, protocols, and trends
• Content Curation: Filters and organizes findings by topic
• Insight Generation: Extracts actionable insights and content angles
• Auto-Save: Stores research in structured markdown files for easy access

Topics Covered

1. Peptides: New peptides, clinical studies, protocols, dosing updates
2. Biohacking Protocols: Emerging techniques, stack combinations, optimization methods
3. Longevity Science: Aging research, interventions, biomarkers, clinical trials
4. Trending Topics: Viral health content, controversial topics, zeitgeist shifts
5. Performance Optimization: Founder health, cognitive enhancement, metabolic optimization

Usage

On-Demand Research

Run a targeted research query:

Run research on [topic] - focus on [specific angle]

Example:

Run research on GLP-1 peptides - focus on recent clinical trials and dosing protocols

Scheduled Research (Heartbeat)

The skill runs automatically via heartbeat rotation, cycling through research topics:

• Peptides (weekly)
• Biohacking protocols (twice weekly)
• Longevity updates (weekly)
• Trending topics (daily)

Output Format

Research is saved to research/[topic]/[date].md:

# [Topic] Research - [Date]

## Key Findings

1. **[Finding Title]**
   - Source: [URL]
   - Key Insight: [1-2 sentence summary]
   - Actionable: [What you can do with this]
   - Content Angle: [How to turn this into content]

2. **[Next Finding]**
   ...

## Trending Discussions

- [Topic]: [Summary of discourse]
- [Topic]: [Summary of discourse]

## Content Ideas Generated

1. [Tweet/thread angle]
2. [LinkedIn post angle]
3. [Article angle]

## Sources Reviewed

- [Source 1]
- [Source 2]
...

Search Strategy

For each research run:

1. Query Construction: Build 3-5 targeted search queries
2. Source Diversity: Mix academic, clinical, and practical sources
3. Recency Filter: Prioritize last 30 days (configurable)
4. Signal Extraction: Identify novel information vs. repetition
5. Content Angle Generation: Translate findings into tweet/post ideas

Integration with Content Creation

Research outputs feed directly into:

• content/biohacker-angles-[date].md (Twitter content)
• content/tokuflow-angles-[date].md (Nattokinase angles)
• notes/research-insights/ (Long-form reference)

Search Queries by Topic

Peptides

• "new peptides 2026"
• "GLP-1 peptides clinical trials"
• "peptide protocols biohacking"
• "BPC-157 latest research"
• "thymosin beta-4 studies"

Biohacking

• "biohacking protocols 2026"
• "founder health optimization"
• "cognitive enhancement stack"
• "metabolic optimization techniques"
• "bloodwork optimization protocols"

Longevity

• "aging research 2026"
• "longevity interventions clinical trials"
• "senolytics latest studies"
• "rapamycin longevity research"
• "NAD+ aging protocols"

Trending

• "health twitter trending"
• "biohacking controversy"
• "peptide discussion twitter"
• "longevity debate 2026"

Filtering Criteria

Include:

• Novel findings (not widely covered)
• Clinical/scientific backing
• Actionable protocols
• Controversial/debate-worthy topics
• Counter-narrative insights

Exclude:

• Generic wellness advice
• Repeated information
• Non-peer-reviewed claims without strong reasoning
• Pure speculation without mechanism

Best Practices

1. Run research before content creation sprints - Fresh angles generate better ideas
2. Review weekly summaries - Track emerging patterns and shifts
3. Cross-reference findings - Connect dots between topics (e.g., peptides + longevity)
4. Archive high-value findings - Move breakthrough research to notes/research-insights/

Manual Research Workflow

When you need deep research on a specific topic:

1. Specify the topic and angle:

   Research [topic] with focus on [specific angle] - find clinical backing and protocols
   

2. Review the output:

   • Check research/[topic]/[date].md
   • Assess signal vs. noise
   • Request refinement if needed

3. Generate content:

   Turn the [specific finding] into 5 tweet angles
   

Heartbeat Integration

To enable scheduled research, add to HEARTBEAT.md:

### 8. Research Automation - Peptides (Priority: Medium)
- Run research-automation skill for peptides
- Focus: New compounds, clinical studies, protocols
- Save to `research/peptides/[date].md`
- Frequency: Once per week

### 9. Research Automation - Trending (Priority: High)
- Run research-automation skill for trending topics
- Focus: Viral health content, debates, controversies
- Save to `research/trending/[date].md`
- Frequency: Daily

Output Locations

workspace/
├── research/
│   ├── peptides/
│   │   └── 2026-02-05.md
│   ├── biohacking/
│   │   └── 2026-02-05.md
│   ├── longevity/
│   │   └── 2026-02-05.md
│   └── trending/
│       └── 2026-02-05.md
└── notes/
    └── research-insights/
        └── breakthrough-findings.md

Tips for Maximizing Value

• Run daily for trending topics - Capture zeitgeist shifts early
• Run weekly for scientific topics - Avoid overwhelming with noise
• Review findings during content planning - Best source of fresh angles
• Cross-pollinate topics - Peptides + longevity = unique positioning
• Archive breakthroughs - High-value findings go to permanent notes

---

Created: 2026-02-05
Last Updated: 2026-02-05