Research any topic across Reddit, X, and web from the last 30 days. Get current trends, real community sentiment, and actionable insights in 7 minutes vs 2 hours manual research.
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name
last30days
description
Research any topic across Reddit, X, and web from the last 30 days. Get current trends, real community sentiment, and actionable insights in 7 minutes vs 2 hours manual research.
Real-time intelligence engine: Find what's working RIGHT NOW, not last quarter.
Scans Reddit, X, and web for the last 30 days, identifies patterns, extracts community insights, and delivers actionable intelligence with copy-paste-ready prompts.
Why This vs ChatGPT?
Problem with "research [topic]": ChatGPT's training data is months/years old. It gives you general knowledge, not current signals.
Problem with Perplexity: Searches web but misses Reddit threads and X conversations where real practitioners share what's actually working.
This skill provides:
30-day freshness filter - Only pulls recent content (not 2023 blog posts)
Multi-platform synthesis - Combines Reddit (detailed discussions), X (real-time signals), and web (articles) in one pass
Pattern detection - Highlights themes mentioned 3+ times across sources
Sentiment analysis - Shows community vibe (hype, skepticism, frustration)
Ready-to-use outputs - Copy-paste prompts and action ideas, not just summaries
You can replicate this by manually searching Reddit, X, and Brave Search with date filters, reading 30+ sources, identifying patterns, and synthesizing insights. Takes 2+ hours. This skill does it in 7 minutes.
When to Use
Perfect for:
Trend discovery - "What's hot in AI agents right now?"
Strategy validation - "What content marketing tactics are working in 2026?"
Competitive intel - "What are developers saying about Cursor vs Copilot?"
Product research - "What do users love/hate about Notion?"
Prompt research - "What Claude prompting techniques are trending?"
Community sentiment - "How do marketers feel about AI tools?"
Not ideal for:
Historical research (use regular search)
Academic/scientific papers (use Google Scholar)
Non-English topics (limited coverage)
Topics with zero online discussion
Required Setup
This skill orchestrates multiple tools. Verify you have:
# 1. Brave Search API (for web_search)# Already configured in OpenClaw by default# 2. Bird CLI (for X/Twitter search)source ~/.openclaw/credentials/bird.env && bird search "test" -n 1
# If this fails, install bird CLI first# 3. Reddit Insights (optional but recommended)# If you have reddit-insights MCP server configured, skill will use it# Otherwise falls back to Reddit web search via Brave
Quick verification:
/last30days --check-setup
Should return:
✅ Brave Search: Available
✅ Bird CLI: Available
✅ Reddit Insights: Available (or "Using web search fallback")
Workflow
Step 1: Web Search (Freshness Filter = Past Month)
# 🔍 /last30days: [TOPIC]*Research compiled: [DATE]**Sources analyzed: [NUMBER] (Reddit threads, X posts, articles)**Time period: Last 30 days*
---
## 🔥 Top Patterns Discovered### 1. [Pattern Name]**Mentioned: X times across [platforms]**
[Description of the pattern + why it matters]
**Key evidence:**- Reddit (r/[sub]): "[Quote from highly upvoted comment]"
- X: "[Quote from popular thread]"
- Article ([Source]): "[Key insight]"
---
### 2. [Pattern Name]
[Continue same format...]
---
## 📊 Reddit Sentiment Breakdown
| Subreddit | Discussion Volume | Sentiment | Key Insight |
|-----------|-------------------|-----------|-------------|
| r/[sub] | [# threads] | 🟢 Positive / 🟡 Mixed / 🔴 Skeptical | [One-liner takeaway] |
**Top upvoted insights:**1. "[Quote]" — u/[username] (+234 upvotes)
2. "[Quote]" — u/[username] (+189 upvotes)
---
## 🐦 X/Twitter Signal Analysis**Trending themes:**- [Theme 1] - [# mentions]
- [Theme 2] - [# mentions]
**Notable voices:**- [@handle]: "[Key take]"
- [@handle]: "[Key take]"
**Engagement patterns:**
[What types of posts are getting traction?]
---
## 📈 Web Article Highlights**Most shared articles:**1. "[Article Title]" — [Source] — [Key insight]
2. "[Article Title]" — [Source] — [Key insight]
**Common recommendations across articles:**- [Tactic 1]
- [Tactic 2]
- [Tactic 3]
---
## 🎯 Copy-Paste Prompt**Based on current community best practices:**
[Ready-to-use prompt incorporating the patterns discovered]
Context: [Relevant context from research]
Task: [Clear task]
Style: [Tone/voice based on research]
Constraints: [Any patterns to avoid based on research]
**Why this works:** [Brief explanation based on research findings]
---
## 💡 Action Ideas
**Immediate opportunities based on this research:**
1. **[Opportunity 1]**
- What: [Specific action]
- Why: [Evidence from research]
- How: [Implementation steps]
2. **[Opportunity 2]**
[Continue format...]
---
## 📌 Source List
**Reddit Threads:**
- [Thread title] - r/[sub] - [URL]
**X Threads:**
- [@handle] - [Tweet] - [URL]
**Articles:**
- [Title] - [Source] - [URL]
---
*Research complete. [X] sources analyzed in [Y] minutes.*
Real Examples
Example 1: Prompt Research
Query:/last30days Claude prompting best practices
Abbreviated Output:
# 🔍 /last30days: Claude Prompting Best Practices## Top Patterns Discovered### 1. XML Tags for Structure (12 mentions)
Reddit and X both emphasize using XML tags for complex prompts:
- Reddit: "XML tags changed my Claude workflow. <context> and <task> make responses 3× more accurate."
- X: "@anthropicAI's own docs now recommend XML. It's the meta."
### 2. Examples Over Instructions (9 mentions)
"Show, don't tell" — Provide 2-3 examples instead of long instructions.
### 3. Chain of Thought Explicit (7 mentions)
Add "Think step-by-step before answering" dramatically improves reasoning.
## Copy-Paste Prompt<context>
[Your context here]
</context><task>
[Your task here]
</task><examples>
Example 1: [Show desired output style]
Example 2: [Show edge case handling]
</examples>
Think step-by-step before providing your final answer.
Example 2: Competitive Intel
Query:/last30days Notion vs Obsidian 2026
Abbreviated Output:
## Top Patterns### 1. "Notion for Teams, Obsidian for Individuals" (18 mentions)
Strong consensus: Notion wins for collaboration, Obsidian wins for personal PKM.
### 2. Performance Complaints About Notion (11 mentions)
"Notion is slow with 1000+ pages" — recurring pain point
## Reddit Sentiment
| Subreddit | Sentiment | Key Insight |
|-----------|-----------|-------------|
| r/Notion | 🟡 Mixed | Love features, frustrated by speed |
| r/ObsidianMD | 🟢 Positive | Passionate community, local-first advocates |
## Action Ideas**If building a PKM tool:**1. Positioning: "Notion speed + Obsidian power" opportunity
2. Target: Teams frustrated by Notion slowness
3. Messaging: "Collaboration without the lag"
Example 3: Content Strategy
Query:/last30days LinkedIn content strategies working 2026
Abbreviated Output:
## Top Patterns### 1. "Teach in Public" Posts Dominate (22 mentions)
Tactical, educational content outperforms thought leadership by 4-5×.
### 2. Carousels Are Fading (14 mentions)
"LinkedIn is deprioritizing carousels" — multiple reports of engagement drops.
### 3. Comment Engagement = Reach (16 mentions)
"Spend 30 min/day commenting on others' posts. Doubled my reach."
## Action Ideas1.**Shift to educational threads** - Format: Problem → Solution (step-by-step) → Result
- Evidence: Posts using this format getting 3-5× more impressions
2.**Abandon carousel strategy** - Data: Engagement down 40-60% since December
3.**Allocate 30 min/day to comments** - Tactic: Comment on posts from your ICP 10 min after posting (algorithm boost)
