last30days

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.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "last30days" with this command: npx skills add brianrwagner/ai-marketing-skills/brianrwagner-ai-marketing-skills-last30days

/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.

Mode

Detect from context or ask: "Quick pulse, full research, or strategic intelligence brief?"

ModeWhat you getBest for
quickReddit only, top 10 insights, 10 minFast topic pulse, content spark
standardReddit + X + web, full synthesis with themesContent planning, market research
deepFull research + strategic brief + content angles + competitive intelligenceProduct decisions, campaign strategy

Default: standard — use quick if they want a fast read. Use deep if they're making a business or product decision.


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:

  1. 30-day freshness filter - Only pulls recent content (not 2023 blog posts)
  2. Multi-platform synthesis - Combines Reddit (detailed discussions), X (real-time signals), and web (articles) in one pass
  3. Pattern detection - Highlights themes mentioned 3+ times across sources
  4. Sentiment analysis - Shows community vibe (hype, skepticism, frustration)
  5. 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)

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

  1. Identify patterns - What appears 3+ times across sources?
  2. Extract key quotes - Most upvoted Reddit comments, retweeted takes
  3. Assess sentiment - Hype, adoption, skepticism, frustration?
  4. 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

  1. Use specific topics - "AI writing tools" better than "AI"
  2. Add context - "for B2B SaaS" or "for developers" narrows results
  3. Run monthly - Track trends over time, spot shifts early
  4. Combine with /reddit-insights - For deeper Reddit analysis
  5. Export to Notion - Keep a trends database
  6. Share with team - Intelligence is more valuable when distributed

Common Use Cases

GoalQuery ExampleOutput Value
Content ideas/last30days AI productivity toolsTopics getting engagement now
Competitive research/last30days Superhuman vs Spark emailUser sentiment, pain points
Positioning/last30days project management frustrationsLanguage customers use
Product validation/last30days AI coding assistant pain pointsReal problems to solve
Marketing tactics/last30days cold email strategies 2026What's working in market

Quality Indicators

A good /last30days report has:

  • 3-5 clear patterns (not just random insights)
  • Quotes from actual users (not just article summaries)
  • Sentiment assessment (what's the vibe?)
  • Ready-to-use prompt (copy-paste quality)
  • Specific action ideas (not vague suggestions)
  • Source links for credibility
  • Recency verified (nothing from >30 days)

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

# Copy skill to your skills directory
cp -r last30days $HOME/.openclaw/skills/

# Verify dependencies
/last30days --check-setup

# First run
/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.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Coding

linkedin-profile-optimizer

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

go-mode

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

meeting-prep-cc

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

tweet-draft-reviewer

No summary provided by upstream source.

Repository SourceNeeds Review