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Reddit Insights

brianrwagner/ai-marketing-claude-code-skills
154 installs313 stars
Summary

Semantic search across millions of Reddit posts when you need to validate product ideas, find user pain points, or research what people actually think about something. Unlike keyword search, this understands intent and can filter by engagement metrics to surface validated discussions. Works best on product comparisons (relevance scores 0.70+), side hustle topics, and tool recommendations where Reddit's debate culture shines. Weaker on abstract concepts or non-English queries. Three modes: quick for a fast pulse check, standard for proper validation with synthesis across multiple queries, and deep for business decisions. Response times run 12-25 seconds. The honest take is that this saves you from manually reading hundreds of posts, but you're still dependent on whether Reddit users have actually discussed your specific topic with enough depth.

Install to Claude Code

npx -y skills add brianrwagner/ai-marketing-claude-code-skills --skill reddit-insights --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

Reddit Insights MCP

Semantic search across millions of Reddit posts. Unlike keyword search, this understands intent and meaning.

Mode

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

ModeWhat you getBest for
quick1 query, top 5 insights, no synthesisFast pain point check, content spark
standard3–5 queries, full synthesis with themes and patternsProduct validation, content research
deepMulti-angle research + sentiment analysis + content angles + competitive intelligenceBusiness decisions, campaign strategy

Default: standard — use quick for a fast read. Use deep if they're validating a product idea or building a content strategy.


Why This vs ChatGPT?

Problem with ChatGPT: It has no real-time Reddit access. It can't search current discussions, can't filter by engagement, and can't show you what people are saying RIGHT NOW about your topic.

This skill provides:

  1. Live semantic search - Searches millions of Reddit posts with AI-powered intent matching (not just keywords)
  2. Engagement filtering - Sort by upvotes/comments to find validated pain points
  3. Sentiment analysis - Automatically tags posts as Discussion/Q&A/Story/News
  4. Relevance scoring - Shows 0-1 match score so you know which results matter
  5. Subreddit intelligence - Browse communities, see trending topics, get recent posts
  6. Direct links - Every result includes Reddit URL for full context

You can replicate this by manually browsing Reddit, searching multiple subreddits, reading hundreds of posts, taking notes, and synthesizing patterns. Takes 1-2 hours per research query. This skill does it in 15-20 seconds.

Setup

1. Get API Key (free tier available)

  1. Sign up at https://reddit-insights.com
  2. Go to Settings → API
  3. Copy your API key

2. Install MCP Server

For Claude Desktop - add to claude_desktop_config.json:

{
  "mcpServers": {
    "reddit-insights": {
      "command": "npx",
      "args": ["-y", "reddit-insights-mcp"],
      "env": {
        "REDDIT_INSIGHTS_API_KEY": "your_api_key_here"
      }
    }
  }
}

For Clawdbot - add to config/mcporter.json:

{
  "mcpServers": {
    "reddit-insights": {
      "command": "npx reddit-insights-mcp",
      "env": {
        "REDDIT_INSIGHTS_API_KEY": "your_api_key_here"
      }
    }
  }
}

Verify installation:

mcporter list reddit-insights

Available Tools

ToolPurposeKey Params
reddit_searchSemantic search across postsquery (natural language), limit (1-100)
reddit_list_subredditsBrowse available subredditspage, limit, search
reddit_get_subredditGet subreddit details + recent postssubreddit (without r/)
reddit_get_trendsGet trending topicsfilter (latest/today/week/month), category

Performance Notes

  • Response time: 12-25 seconds (varies by query complexity)
    • Simple queries: ~12-15s
    • Complex semantic queries: ~17-20s
    • Heavy load periods: up to 25s
  • Best results: Specific products, emotional language, comparison questions
  • Weaker results: Abstract concepts, non-English queries, generic business terms
  • Sweet spot: Questions a real person would ask on Reddit

Best Use Cases (Tested)

Use CaseEffectivenessWhy
Product comparisons (A vs B)⭐⭐⭐⭐⭐Reddit loves debates
Tool/app recommendations⭐⭐⭐⭐⭐High-intent discussions
Side hustle/money topics⭐⭐⭐⭐⭐Engaged communities
Pain point discovery⭐⭐⭐⭐Emotional posts rank well
Health questions⭐⭐⭐⭐Active health subreddits
Technical how-to⭐⭐⭐Better to search specific subreddits
Abstract market research⭐⭐Too vague for semantic search
Non-English queries⭐Reddit is English-dominant

Query Strategies (Tested with Real Data)

✅ Excellent Queries (relevance 0.70+)

Product Comparisons (best results!):

"Notion vs Obsidian for note taking which one should I use"
→ Relevance: 0.72-0.81 | Found: Detailed comparison discussions, user experiences

"why I switched from Salesforce to HubSpot honest experience"  
→ Relevance: 0.70-0.73 | Found: Migration stories, feature comparisons

Side Hustle/Money Topics:

"side hustle ideas that actually make money not scams"
→ Relevance: 0.70-0.77 | Found: Real experiences, specific suggestions

Niche App Research:

"daily horoscope apps which one is accurate and why"
→ Relevance: 0.67-0.72 | Found: App recommendations, feature requests

✅ Good Queries (relevance 0.60-0.69)

Pain Point Discovery:

"I hate my current CRM it is so frustrating"
→ Relevance: 0.60-0.64 | Found: Specific CRM complaints, feature wishlists

"cant sleep at night tried everything what actually works"
→ Relevance: 0.60-0.63 | Found: Sleep remedies discussions, medical advice seeking

Tool Evaluation:

"AI tools that actually save time not just hype"
→ Relevance: 0.64-0.65 | Found: Real productivity gains, tool recommendations

❌ Weak Queries (avoid these patterns)

Too Abstract:

"business opportunity growth potential"
→ Relevance: 0.52-0.58 | Returns unrelated generic posts

Non-English:

"学习编程最好的方法" (Chinese)
→ Relevance: 0.45-0.51 | Reddit is English-dominant, poor cross-lingual results

Query Formula Cheat Sheet

GoalPatternRelevance
Compare products"[Product A] vs [Product B] which should I use"0.70-0.81
Find switchers"why I switched from [A] to [B]"0.70-0.73
Money/hustle topics"[topic] that actually [works/makes money] not [scam/hype]"0.70-0.77
App recommendations"[category] apps which one is [accurate/best] and why"0.67-0.72
Pain points"I hate my current [tool] it is so [frustrating/slow]"0.60-0.64
Solutions seeking"[problem] tried everything what actually works"0.60-0.63

Response Fields

Each result includes:

  • title, content - Post text
  • subreddit - Source community
  • upvotes, comments - Engagement metrics
  • relevance (0-1) - Semantic match score (0.5+ is good, 0.6+ is strong)
  • sentiment - Discussion/Q&A/Story Sharing/Original Content/News
  • url - Direct Reddit link

Example response:

{
  "id": "1oecf5e",
  "title": "Trying to solve the productivity stack problem",
  "content": "The perfect productivity app doesn't exist. No single app can do everything well, so we use a stack of apps. But this creates another problem: multi app fragmentation...",
  "subreddit": "productivityapps",
  "upvotes": 1,
  "comments": 0,
  "relevance": 0.631,
  "sentiment": "Discussion",
  "url": "https://reddit.com/r/productivityapps/comments/1oecf5e"
}

Real Case Study

User: SaaS founder validating a new project management tool idea

Challenge: Needed to understand real frustrations with existing PM tools (Asana, Monday, ClickUp) to find positioning angle.

Research Query:

reddit_search("I hate my project management tool it's so frustrating for remote teams", limit=50)

What They Found (in 18 seconds):

  • 42 posts with 0.60+ relevance
  • Top pain points (mentioned 15+ times):
    • "Too complicated for simple projects"
    • "Mobile app is terrible"
    • "Hard to see the big picture"
    • "Notifications are overwhelming"
    • "Pricing jumps too fast with team size"

Most upvoted insight (+347 upvotes, r/startups):

"We switched from Monday to a Notion template because Monday felt like learning a new language just to assign a task. Sometimes simple beats powerful."

Positioning Decision: Built messaging around: "Project management that feels like a shared doc, not enterprise software."

Product Changes Made:

  • Simplified onboarding (3 clicks to first task vs 15-step wizard)
  • Mobile-first design (every feature tested on phone first)
  • Flat pricing ($8/user, no tiers)
  • Big-picture dashboard view (Gantt hidden by default)

Results (6 months post-launch):

  • 2,400 paying users
  • 78% came from "Reddit research-informed" messaging
  • 4.7/5 rating on G2 with reviews saying "finally, PM without the bloat"
  • Founder quote: "That one Reddit search saved us from building features nobody wanted."

Tips

  1. Natural language works best - Ask questions like a human would
  2. Include context - "for small business" or "as a developer" improves results
  3. Combine emotion words - "frustrated", "love", "hate", "wish" find stronger opinions
  4. Filter by engagement - High upvotes/comments = validated pain points
  5. Check multiple subreddits - Same topic discussed differently in r/startups vs r/smallbusiness
  6. Use comparison queries - "X vs Y" consistently returns high-relevance results
  7. Search for stories - "why I switched" and "honest experience" reveal real user journeys

Example Workflows

Find SaaS opportunity:

  1. reddit_search: "frustrated with project management tools for remote teams"
  2. Filter results with high engagement (20+ upvotes or 10+ comments)
  3. Identify recurring complaints → product opportunity
  4. Export top 10 posts to analyze language patterns for messaging

Validate idea:

  1. reddit_search: "[your product category] recommendations"
  2. See what alternatives people mention
  3. Note gaps in existing solutions
  4. Check reddit_get_subreddit for relevant communities to monitor

Content research:

  1. reddit_get_subreddit: Get posts from target community
  2. reddit_search: Find specific questions/discussions with high engagement
  3. Create content answering real user questions (with examples from Reddit)
  4. Post back to Reddit (with value, not spam)

Competitive intelligence:

  1. reddit_search: "[competitor name] experience"
  2. reddit_search: "switched from [competitor] to [other]"
  3. Extract feature complaints and praise
  4. Build comparison matrix based on real feedback

Pro Tips

For Product Research:

  • Search for "I wish [category] had..." to find feature requests
  • Filter by comments (not just upvotes) to find discussion-heavy threads
  • Look for posts from 30-90 days ago (recent but with accumulated discussion)

For Content Ideas:

  • Search your topic + "explained" or "guide"
  • Check what questions have 0-2 replies (content gaps!)
  • Save high-upvote posts and create better answers

For Market Validation:

  • Run the same search monthly to track sentiment trends
  • Compare subreddit sizes (r/notion has 180K vs r/obsidianmd 90K)
  • Watch for "migration posts" ("leaving X for Y") as early signals

Quality Indicators

A good Reddit Insights search has:

  • Relevance scores mostly 0.60+ (strong semantic match)
  • Results from 3+ different subreddits (diverse perspectives)
  • Mix of high engagement (100+ upvotes) and niche discussions
  • Clear patterns across multiple posts (not one-off opinions)
  • Recent posts (<90 days) mixed with classic threads

Common Mistakes to Avoid

❌ Being too generic - "marketing tips" returns weak results; "B2B cold email that actually works" is better ❌ Ignoring engagement metrics - A post with 2 upvotes is one person's opinion; 200+ upvotes is validated ❌ Taking single posts as truth - Look for patterns across 5-10 posts minimum ❌ Forgetting to check sentiment - A "Discussion" post is different from a "Q&A" (check the field!) ❌ Not visiting actual threads - The semantic summary is great, but top comments often have gold


Built on semantic AI search (not keyword matching). Find what people REALLY think. Not what marketing says they think.

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Categories
AI & Agent BuildingMarketing & SEO
First SeenJun 3, 2026
View on GitHub

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