AI Research Automation: Monitor Reddit and X for Trends

AI Research Automation: Monitor Reddit and X for Trends

You need to know what's trending.

What are people talking about? What problems are they complaining about? What competitors are doing well?

This information exists. It's on Reddit. It's on X. It's in thousands of threads you don't have time to read.

Here's how to automate it.

The Manual Way (Don't Do This)

Every day, you:

1. Open Reddit
2. Check 5-10 subreddits
3. Sort by top/week
4. Read through threads
5. Take notes
6. Open X
7. Search your keywords
8. Check engagement
9. Read through replies
10. Take more notes

Time spent: 1-2 hours. Value extracted: Partial. You missed things.

The Automated Way

Install a research skill. Tell it what to monitor. Get reports delivered.

One skill that does this well: the "Last 30 Days" research skill.

It:

• Searches Reddit and X in parallel
• Filters by engagement (viral threads only)
• Extracts key insights
• Formats into a readable report

What used to take 2 hours takes 30 seconds.

Setting It Up

Step 1: Install the skill

Give your OpenClaw the skill URL:

Please install this skill: [skill URL]

It will download and configure the skill automatically.

Step 2: Configure API access

The skill needs:

• xAI API (Grok) for X access
• OpenAI API for Reddit access

Add these to your agent's configuration.

Step 3: Run a test query

Use the last 30 days skill to find information about "AI agents for productivity"

You'll get a report with:

• Top Reddit threads by engagement
• Top X posts by engagement
• Key themes and insights
• Content opportunities

What the Report Looks Like

# Research Report: AI Agents for Productivity

## Reddit Findings (Last 30 Days)

### Top Threads by Engagement

1. r/ChatGPT - "I automated my entire morning routine" (2.4k upvotes)
   - Key insight: People want voice-activated workflows
   - Sentiment: Positive, but concerns about reliability

2. r/LocalLLaMA - "Running agents on M3 Mac Mini" (1.8k upvotes)
   - Key insight: Hardware recommendations needed
   - Sentiment: Excited but confused about setup

3. r/artificial - "AI agents are overhyped" (1.2k upvotes)
   - Key insight: Counter-narrative exists
   - Sentiment: Skeptical, wants proof

### Emerging Themes
- Local deployment vs cloud
- Security concerns growing
- Cost optimization discussions

## X Findings (Last 30 Days)

### Top Posts by Engagement

1. @techinfluencer - "Here's my full OpenClaw setup" (45k impressions)
   - Format: Thread with screenshots
   - Hook: "This saved me 10 hours/week"

2. @founder - "AI agents changed my business" (32k impressions)
   - Format: Story post
   - Hook: Personal transformation

3. @developer - "The dark side of AI agents" (28k impressions)
   - Format: Warning/educational
   - Hook: Security concerns

### Content Opportunities
- Tutorial content performing well
- "Setup guide" format has high engagement
- Security angle is underserved

## Recommendations

1. Create a "complete setup guide" thread
2. Address security concerns explicitly
3. Show real results with screenshots

This took 30 seconds to generate. Manually? 2 hours minimum.

Scheduling Regular Research

Don't run research manually. Schedule it.

Every Monday at 9 AM, run a research report on:
- "OpenClaw" - what's the community saying
- "AI productivity" - general trends
- [competitor name] - what are they doing

Save to my second brain. Include in weekly review.

Now you have automated competitive intelligence.

Custom Research Queries

The skill is flexible. Some queries that work well:

Competitor Monitoring:

Research what people are saying about [competitor] in the last 30 days.
Focus on complaints, praise, and feature requests.

Content Ideas:

Find the top performing content about [topic] on Reddit and X.
Extract the hooks, formats, and angles that worked.

Problem Discovery:

Research the biggest complaints about [category] in the last 30 days.
Identify problems people would pay to solve.

Trend Spotting:

Find emerging topics in [niche] that are gaining traction
but aren't saturated yet.

Integrating with Morning Briefs

The research skill becomes powerful when combined with your morning brief:

Include in my morning brief:
- Top 3 trending topics in my niche from last 24 hours
- Any viral content from competitors
- Emerging opportunities from Reddit/X research

Now you wake up with market intelligence delivered automatically.

The Content Pipeline

Here's how one creator uses this:

Monday:

• Research report generates for the week
• Identifies 5 potential content topics

Tuesday-Wednesday:

• Deep dive on top 2 topics
• Agent researches specific angles

Thursday:

• Script generated based on research
• Competitor approaches included for differentiation

Friday:

• Record and publish
• Performance tracked for next week's research

The research informs the content. The content performance informs the research. Feedback loop.

Skill Security Note

Research skills need API access. This means:

• API keys stored in your agent
• Network access to external services
• Data flows through third parties

Best practices:

1. Use dedicated API keys (not your main account)
2. Set usage limits on the keys
3. Review the skill code before installing
4. Monitor API usage for anomalies

Why Clawctl for Research Automation

Research automation needs to run consistently. At 9 AM every Monday. Without fail.

Self-hosted challenges:

• Server might be down
• API keys might expire
• Skills might break
• No alerts when things fail

Clawctl handles:

Your research runs. Every time. Without babysitting.

Get Started

1. Deploy OpenClaw on Clawctl
2. Install a research skill
3. Configure your topics
4. Schedule weekly reports
5. Never manually research again

The information exists. Your competitors are reading it. Now you are too—automatically.

Deploy AI research automation →

Learn about morning briefs →