| 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. |
| version | 2.0.0 |
| author | theflohart |
| tags | ["research","trends","reddit","twitter","competitive-intel","content-research"] |
/last30days Research Skill
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:
source ~/.openclaw/credentials/bird.env && bird search "test" -n 1
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)
web_search: "[topic] 2026" + freshness=pm
web_search: "[topic] strategies trends current"
web_search: "[topic] what's working"
Purpose: Get recent articles, blog posts, tools
Step 2: Reddit Search
If reddit-insights MCP configured:
reddit_search: "[topic] discussions techniques"
reddit_get_trends: "[subreddit]"
Otherwise:
web_search: "[topic] site:reddit.com" + freshness=pm
web_search: "[topic] reddit.com/r/[relevant_sub]"
Purpose: Find detailed discussions, practitioner insights, "what's actually working" threads
Step 3: X/Twitter Search
bird search "[topic]" -n 10
bird search "[topic] 2026" -n 10
bird search "[topic] best practices" -n 10
Purpose: Real-time signals, expert takes, trending threads
Step 4: Deep Dive on Top Sources (Optional)
For the 2-3 most relevant links:
web_fetch: [article URL]
Purpose: Extract specific tactics, quotes, data points
Step 5: Synthesize & Package
- Identify patterns - What appears 3+ times across sources?
- Extract key quotes - Most upvoted Reddit comments, retweeted takes
- Assess sentiment - Hype, adoption, skepticism, frustration?
- Create ready-to-use outputs - Prompts, action ideas, copy-paste tactics
Output Template
# 🔍 /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 Ideas
1. **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)
Real Case Study
User: B2B SaaS marketer researching content trends quarterly
Before using skill:
- Manual research: 2-3 hours per topic
- Visited 20-30 sites, took scattered notes
- Hard to identify patterns across sources
- No systematic approach
After implementing /last30days:
- Research time: 7-10 minutes per topic
- Consistent output format (easy to reference later)
- Pattern detection automatic
- Copy-paste prompts immediately usable
Impact after 3 months:
- 10 trend reports created (vs 2-3 before)
- Content strategy pivots based on current signals, not guesses
- Team shares research reports across org (became go-to intelligence source)
- Time saved: ~20 hours/month
Quote: "I used to spend half a day researching trends, now it's 7 minutes. The pattern detection alone is worth it—I'd miss things reading manually."
Configuration Options
Standard Mode (default)
/last30days [topic]
- Searches web, Reddit, X
- Synthesizes top patterns
- Generates prompts + action ideas
Deep Dive Mode
/last30days [topic] --deep
- Fetches and analyzes top 5 articles in full
- More detailed quotes and data points
- Takes 12-15 minutes instead of 7
Reddit-Only Mode
/last30days [topic] --reddit-only
- Focuses exclusively on Reddit discussions
- Best for: Community sentiment, practitioner insights
Quick Brief Mode
/last30days [topic] --quick
- Top 3 patterns only
- No detailed synthesis
- 3-minute output
Pro Tips
- Use specific topics - "AI writing tools" better than "AI"
- Add context - "for B2B SaaS" or "for developers" narrows results
- Run monthly - Track trends over time, spot shifts early
- Combine with /reddit-insights - For deeper Reddit analysis
- Export to Notion - Keep a trends database
- Share with team - Intelligence is more valuable when distributed
Common Use Cases
| Goal | Query Example | Output Value |
|---|
| Content ideas | /last30days AI productivity tools | Topics getting engagement now |
| Competitive research | /last30days Superhuman vs Spark email | User sentiment, pain points |
| Positioning | /last30days project management frustrations | Language customers use |
| Product validation | /last30days AI coding assistant pain points | Real problems to solve |
| Marketing tactics | /last30days cold email strategies 2026 | What's working in market |
Quality Indicators
A good /last30days report has:
Limitations
This skill does NOT:
- Access paywalled content (uses public sources only)
- Provide academic-quality research (for speed, not depth)
- Replace domain expertise (synthesizes existing knowledge)
- Guarantee completeness (samples popular discussions)
Best for: Fast, directional intelligence. Not dissertation-level research.
Installation
cp -r last30days $HOME/.openclaw/skills/
/last30days --check-setup
/last30days "your topic here"
Support
Issues or missing sources? Provide:
- Topic searched
- Expected vs actual sources found
- Any error messages
- Your setup verification output
Built to replace 2-hour research sessions with 7-minute intelligence reports.
Know what's working RIGHT NOW. Not last quarter. Not last year. Today.
