
Last30days
- 260 installs
- 390 repo stars
- Updated March 19, 2026
- brianrwagner/ai-marketing-claude-code-skills
Research marketing trends, competitor moves, and audience signals from the past 30 days to inform campaigns, positioning, and timely content decisions.
About
AI marketing skill for analyzing the last 30 days of trends, competitor activity, and audience signals to guide timely campaigns, positioning updates, and content priorities for growth-focused teams.
- Recent trend scanning
- Competitive signal review
- Campaign timing insights
- Audience interest patterns
- Marketing research briefs
Last30days by the numbers
- 260 all-time installs (skills.sh)
- Ranked #882 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 260 |
|---|---|
| repo stars | ★ 390 |
| Last updated | March 19, 2026 |
| Repository | brianrwagner/ai-marketing-claude-code-skills ↗ |
What it does
Research marketing trends, competitor moves, and audience signals from the past 30 days to inform campaigns, positioning, and timely content decisions.
Files
/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?"
| Mode | What you get | Best for |
|---|---|---|
quick | Reddit only, top 10 insights, 10 min | Fast topic pulse, content spark |
standard | Reddit + X + web, full synthesis with themes | Content planning, market research |
deep | Full research + strategic brief + content angles + competitive intelligence | Product 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 BraveQuick verification:
/last30days --check-setupShould 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 10Purpose: 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
| 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:
- [ ] 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.
Last 30 Days Research
Know what's working RIGHT NOW, not last quarter.
7-minute trend reports across Reddit, X, and web. Real community sentiment. Actionable intelligence. Copy-paste-ready prompts.
The Problem
You need to know what's working NOW:
- Google Search → Articles from 2022-2023 (outdated)
- ChatGPT → Training data months/years old (generic advice)
- Manual research → 2-3 hours reading 30+ sources (exhausting)
- Perplexity → Searches web but misses Reddit + X conversations
Result: You make decisions based on old information or spend hours researching manually.
The Solution
/last30days - Multi-platform intelligence engine with 30-day freshness filter.
What You Get
✅ 30-day recency - Only recent content, not 2023 blog posts ✅ Multi-platform synthesis - Reddit (discussions) + X (signals) + Web (articles) in one pass ✅ Pattern detection - Highlights themes mentioned 3+ times ✅ Sentiment analysis - Community vibe (hype, skepticism, working) ✅ Copy-paste outputs - Ready prompts and action ideas ✅ 7-minute reports - vs 2-3 hours manual research
Why This vs Alternatives?
| Tool | Coverage | Recency | Synthesis | Speed |
|---|---|---|---|---|
| Google Search | Web only | Mixed | None | Manual |
| Perplexity | Web + some forums | Good | Some | Fast |
| ChatGPT | Knowledge cutoff | Old | Good | Fast |
| Manual Reddit | Reddit only | Good | Manual | Slow |
| This skill | Reddit + X + Web | 30 days | Auto | 7 min |
Real Results
B2B SaaS marketer (3 months using skill):
- Research time: 2-3 hrs/topic → 7-10 min/topic
- Reports created: 2-3/quarter → 10/quarter
- Time saved: ~20 hours/month
- Team impact: Became go-to intelligence source
Quote: "I'd miss patterns reading manually. The skill catches things across platforms I'd never connect."
Quick Start
Install
cp -r last30days $HOME/.openclaw/skills/Verify Setup
/last30days --check-setupShould show:
- ✅ Brave Search: Available
- ✅ Bird CLI: Available (for X)
- ✅ Reddit Insights: Available or fallback
Use
# Standard research
/last30days "AI prompting best practices"
# Deep dive (fetches full articles)
/last30days "Notion vs Obsidian" --deep
# Reddit-focused
/last30days "cold email strategies" --reddit-only
# Quick brief (top 3 patterns)
/last30days "content marketing trends" --quickExample Outputs
Example 1: Prompt Research
Query: /last30days Claude prompting techniques
Output (abbreviated):
## Top Patterns Discovered
1. **XML Tags for Structure** (12 mentions)
- "XML tags changed my workflow. 3× more accurate."
- Anthropic's own docs now recommend this
2. **Examples Over Instructions** (9 mentions)
- "Show, don't tell" — 2-3 examples beat long instructions
3. **Chain of Thought** (7 mentions)
- "Think step-by-step" improves reasoning quality
## Copy-Paste Prompt
<context>[Your context]</context>
<task>[Your task]</task>
<examples>
Example 1: [Show output style]
Example 2: [Edge case]
</examples>
Think step-by-step before answering.---
Example 2: Competitive Intel
Query: /last30days Cursor vs GitHub Copilot developers
Output (abbreviated):
## Reddit Sentiment
| Subreddit | Sentiment | Key Insight |
|-----------|-----------|-------------|
| r/programming | 🟢 Positive on Cursor | "Cursor's context awareness is unmatched" |
| r/vscode | 🟡 Mixed | "Copilot cheaper, Cursor smarter" |
## Action Ideas
1. **Positioning opportunity:** "Context-aware coding" angle resonating
2. **Pain point:** Developers frustrated by Copilot's limited context
3. **Messaging:** "Understands your entire codebase, not just one file"---
Example 3: Content Strategy
Query: /last30days LinkedIn content strategies 2026
Output (abbreviated):
## Top Patterns
1. **"Teach in Public" posts dominate** (22 mentions)
- Educational content > thought leadership by 4-5×
2. **Carousels are fading** (14 mentions)
- Engagement down 40-60% since December
3. **Comment engagement = reach** (16 mentions)
- "30 min/day commenting doubled my impressions"
## Action Ideas
- Shift to educational threads (Problem → Solution → Result)
- Abandon carousels (algo deprioritizing)
- Allocate 30 min/day to strategic commentingWhat Makes This Powerful
1. Multi-Platform Pattern Detection
Finds themes across:
- Reddit - Detailed discussions, practitioner experiences ("here's what worked")
- X/Twitter - Real-time signals, expert takes, trending conversations
- Web - Recent articles, data, tactical guides
2. Automatic Synthesis
You don't read 30 sources manually. The skill:
- Identifies patterns (mentioned 3+ times)
- Extracts key quotes (highly upvoted, retweeted)
- Assesses sentiment (hype, adoption, skepticism)
- Creates actionable outputs (prompts, ideas)
3. 30-Day Freshness Filter
Only recent content:
- Web search:
freshness=pm(past month) - Reddit: Last 30 days filter
- X: Current trending discussions
No 2022 blog posts. No outdated tactics. Current intelligence only.
Common Use Cases
| Goal | Example Query | Value |
|---|---|---|
| Content ideas | "AI productivity tools" | Topics getting engagement NOW |
| Competitive research | "Notion vs Coda users" | User sentiment, pain points |
| Positioning | "project management frustrations" | Language customers actually use |
| Product validation | "AI writing tool pain points" | Real problems to solve |
| Marketing tactics | "cold outreach working 2026" | What's working in market |
Modes
Standard Mode (7 min)
/last30days "topic"- Web + Reddit + X synthesis
- Top patterns + prompts + actions
Deep Dive Mode (12-15 min)
/last30days "topic" --deep- Fetches top 5 full articles
- More detailed quotes and data
Reddit-Only Mode (5 min)
/last30days "topic" --reddit-only- Focus exclusively on Reddit
- Best for: Community sentiment
Quick Brief Mode (3 min)
/last30days "topic" --quick- Top 3 patterns only
- No deep synthesis
Output Structure
Every report includes:
1. Top Patterns - Themes mentioned 3+ times 2. Reddit Sentiment - Subreddit discussions + top quotes 3. X/Twitter Signal - Trending themes + notable voices 4. Web Highlights - Most shared articles + common tactics 5. Copy-Paste Prompt - Ready to use based on research 6. Action Ideas - Specific opportunities with evidence 7. Source List - All links for verification
Pro Tips
1. Be specific - "AI writing tools for marketers" > "AI" 2. Add context - "for B2B SaaS" or "for developers" helps 3. Run monthly - Track trends, spot shifts early 4. Export to Notion - Build a trends database 5. Share with team - Intelligence is valuable when distributed
Who This Is For
✅ Marketers - Content trends, messaging, positioning ✅ Product managers - User pain points, competitive intel ✅ Founders - Market validation, strategy signals ✅ Content creators - What's resonating, fresh angles ✅ Strategists - Current tactics, community sentiment
Requirements
- Brave Search API - Built into OpenClaw (no setup)
- Bird CLI - For X/Twitter search (install if needed)
- Reddit Insights - Optional MCP server (falls back to web if unavailable)
Verify with: /last30days --check-setup
What You'll Notice After Using This
- ✅ Decisions based on current data, not guesses
- ✅ Pattern recognition you'd miss reading manually
- ✅ Research time cut by 85% (2+ hours → 7 minutes)
- ✅ Copy-paste-ready outputs (no further synthesis needed)
- ✅ Team starts asking you for trend intelligence
Limitations
This skill does NOT:
- Access paywalled content (public sources only)
- Provide academic-level depth (speed over exhaustiveness)
- Replace domain expertise (synthesizes existing knowledge)
- Guarantee 100% completeness (samples popular discussions)
Best for: Fast, directional intelligence for decisions and strategy.
Installation & Usage
# Install
cp -r last30days $HOME/.openclaw/skills/
# Verify setup
/last30days --check-setup
# First research
/last30days "your topic"
# Deep dive
/last30days "your topic" --deep
# Quick brief
/last30days "your topic" --quickComing Soon
- Trend tracking - Compare month-over-month patterns
- Export to Notion - One-click trend database sync
- Slack integration - Auto-post weekly trend reports
- Custom source weights - Prioritize Reddit vs X vs Web
License
MIT License - Use freely, commercially or personally.
Contributing
Improvements or new data sources? Submit via GitHub issues.
Built by theflohart to replace 2-hour research sessions with 7-minute intelligence.
---
Stop relying on old information.
7-minute trend reports. Current signals. Actionable intelligence.
Platform: OpenClaw (token-optimized)
Mode
| Mode | Output | Use when |
|---|---|---|
quick | Reddit only, top 10 insights | Fast topic pulse |
standard | Reddit + X + web, full synthesis | Default — content/market research |
deep | Full + strategic brief + content angles + competitive intel | Product decisions, campaign strategy |
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"Step 2 — Reddit search: If reddit-insights MCP configured:
reddit_search: "[topic] discussions techniques"Otherwise:
web_search: "[topic] site:reddit.com" + freshness=pmStep 3 — X/Twitter search:
bird search "[topic]" -n 10
bird search "[topic] 2026" -n 10Step 4 — Deep dive on top 2-3 sources:
web_fetch: [article URL]Step 5 — Synthesize:
- Identify patterns appearing 3+ times across sources
- Extract key quotes (most upvoted Reddit, retweeted takes)
- Assess sentiment (hype / adoption / skepticism / frustration)
- Create copy-paste prompts + action ideas
Output Format
# 🔍 /last30days: [TOPIC]
*Sources: [N] | Period: Last 30 days | Date: [DATE]*
## 🔥 Top Patterns
### 1. [Pattern Name] — mentioned X times
[Description + key evidence]
- Reddit: "[Quote]"
- X: "[Quote]"
- Article: "[Key insight]"
## 📊 Sentiment Breakdown
[Platform | Volume | Sentiment | Key Insight]
## 🎯 Copy-Paste Prompt
[Ready-to-use prompt incorporating research findings]
## 💡 Action Ideas
1. [Opportunity + evidence + how]
## 📌 Sources
[Reddit threads, X threads, Articles with URLs]Quality Checklist
- [ ] 3–5 clear patterns (not random insights)
- [ ] Quotes from actual users
- [ ] Sentiment assessed
- [ ] Ready-to-use prompt (copy-paste quality)
- [ ] Specific action ideas (not vague suggestions)
- [ ] All sources from last 30 days
--- Skill by theflohart | AI Marketing Skills
Related skills
Forks & variants (1)
Last30days has 1 known copy in the catalog totaling 150 installs. They canonicalize to this original listing.
- brianrwagner - 150 installs