reddit-research v2026-02-23A

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---
name: reddit-research
version: 2026-02-23
description: Search and analyze Reddit discussions for market research, product feedback, and community insights using Xpoz. Use when asked to "search Reddit", "what does Reddit think about X", "Reddit feedback on X", "subreddit analysis", or "Reddit market research".
---

# Reddit Research

## Overview

Search and analyze Reddit discussions across all subreddits. Extract community opinions, identify pain points, discover product feedback, and understand market sentiment — all without Reddit API keys.

## When to Use

Activate when the user asks:
- "What does Reddit think about [PRODUCT]?"
- "Search Reddit for [TOPIC]"
- "What are people saying about [BRAND] on Reddit?"
- "Reddit feedback on [TOOL/SERVICE]"
- "Find Reddit discussions about [TOPIC]"
- "Market research on Reddit for [INDUSTRY]"

## Setup & Authentication

Before fetching data, verify Xpoz access is configured. Try them in order:

### Check 1: MCP Server (preferred)
If you have MCP tool access, check if `xpoz` tools are available (e.g., `getTwitterPostsByKeywords`). If yes, authentication is already handled — skip to Step 1.

### Check 2: SDK via Environment Variable
```bash
echo $XPOZ_API_KEY
```
If set, the SDK will authenticate automatically:
```python
from xpoz import XpozClient
client = XpozClient()  # auto-reads XPOZ_API_KEY
```

### Check 3: Nothing Configured
If neither MCP nor env var is available, ask the user to:
1. Get a free API key at [xpoz.ai/get-token](https://xpoz.ai/get-token?utm_source=github&utm_medium=agent-skills&utm_campaign=reddit-research) (100K results/month free)
2. Then EITHER:
   - **Set env var:** `export XPOZ_API_KEY=<their-key>` and use the SDK
   - **Configure MCP:** Add to `~/.claude.json` (or agent's MCP config):
     ```json
     {
       "mcpServers": {
         "xpoz": {
           "url": "https://mcp.xpoz.ai/mcp",
           "transport": "http-stream",
           "headers": { "Authorization": "Bearer <their-key>" }
         }
       }
     }
     ```
   - **Pass directly:** `XpozClient("<their-key>")` in Python or `new XpozClient({ apiKey: "<their-key>" })` in TypeScript

### Auth Errors
If you get `AuthenticationError` or 401 responses:
- Verify the API key is valid at [xpoz.ai/settings](https://xpoz.ai/settings)
- Check the key hasn't expired
- Ensure no extra whitespace in the key


## Step-by-Step Instructions

### Step 1: Parse the Request

Extract:
- **Topic/product/brand** to research
- **Specific questions** the user wants answered
- **Time period** (default: last 30 days)
- **Subreddit filter** (if user specifies one)

Build the query:
- Product name + common alternatives: `"Cursor" OR "Cursor IDE" OR "cursor.sh"`
- Include comparison terms: `"Cursor vs" OR "Cursor alternative"`
- For feedback: `"Cursor" AND ("love" OR "hate" OR "switched" OR "review")`

### Step 2: Fetch Reddit Posts

#### Via MCP

```
Call getRedditPostsByKeywords:
  query: "<expanded query>"
  fields: ["id", "title", "text", "authorUsername", "createdAtDate", "score", "numComments", "subreddit", "url"]
  startDate: "<30 days ago, YYYY-MM-DD>"
  endDate: "<today, YYYY-MM-DD>"
```

**CRITICAL:** Call `checkOperationStatus` with the returned `operationId` and poll until "completed" (up to 8 retries, ~5 seconds apart).

**For users who posted about the topic:**
```
Call getRedditUsersByKeywords:
  query: "<query>"
  fields: ["id", "username", "relevantPostsCount"]
  startDate: "<30 days ago>"
```

#### Via Python SDK

```python
from xpoz import XpozClient

client = XpozClient()

# Search Reddit posts
results = client.reddit.search_posts(
    '"Cursor" OR "Cursor IDE"',
    start_date="2026-01-24",
    end_date="2026-02-23",
    fields=["id", "title", "text", "author_username", "created_at_date", "score", "num_comments", "subreddit", "url"]
)

# Collect all pages
all_posts = results.data
while results.has_next_page():
    results = results.next_page()
    all_posts.extend(results.data)

print(f"Found {len(all_posts)} Reddit posts")

# Export to CSV for deeper analysis
csv_url = results.export_csv()

client.close()
```

#### Via TypeScript SDK

```typescript
import { XpozClient } from "xpoz";

const client = new XpozClient();
await client.connect();

const results = await client.reddit.searchPosts('"Cursor" OR "Cursor IDE"', {
  startDate: "2026-01-24",
  endDate: "2026-02-23",
  fields: ["id", "title", "text", "authorUsername", "createdAtDate", "score", "numComments", "subreddit", "url"],
});

console.log(`Found ${results.pagination.totalRows} posts`);
const csvUrl = await results.exportCsv();

await client.close();
```

### Step 3: Analyze the Data

**Subreddit Distribution:**
- Group posts by subreddit
- Identify where the most discussion happens
- Note subreddit context (r/programming = developers, r/productivity = end users, etc.)

**Sentiment Analysis:**
- Reddit uses upvotes/downvotes as built-in sentiment (high score = community agrees)
- Posts with high `numComments` indicate controversial or engaging topics
- Score/comments ratio: high score + few comments = consensus; low score + many comments = debate

**Theme Extraction:**
Identify recurring themes:
- **Pain points**: complaints, frustrations, feature requests
- **Praise**: what users love, competitive advantages
- **Comparisons**: how the product compares to alternatives
- **Use cases**: how people actually use the product
- **Questions**: common confusion points or information gaps

**Tip:** Reddit posts often contain more nuanced, detailed opinions than Twitter. Prioritize posts with high `score` and `numComments` for quality insights.

### Step 4: Generate Report

```
## Reddit Research: [TOPIC]
**Period:** [date range] | **Posts analyzed:** [count]

### Overview
[2-3 sentence summary of what Reddit thinks]

### Subreddit Distribution
| Subreddit | Posts | Avg Score | Top Theme |
|-----------|-------|-----------|-----------|
| r/programming | X | X | Performance concerns |
| r/productivity | X | X | Workflow improvements |
| ... | ... | ... | ... |

### Key Themes

#### 1. 👍 What People Love
- [Theme with supporting quotes]
- [Theme with supporting quotes]

#### 2. 👎 Pain Points & Complaints
- [Theme with supporting quotes]
- [Theme with supporting quotes]

#### 3. 🔄 Comparisons & Alternatives
- [Product vs Competitor: community consensus]
- [Common alternatives mentioned]

#### 4. 💡 Feature Requests & Suggestions
- [Most requested features]
- [Creative use cases discovered]

### Top Posts (by engagement)
| Score | Comments | Subreddit | Title |
|-------|----------|-----------|-------|
| 1.2K | 234 | r/programming | "Title..." |
| ... | ... | ... | ... |

### Notable Quotes
> "Actual Reddit quote with context" — u/username in r/subreddit (⬆️ 456)

### Actionable Insights
[3-5 bullet points of what to do with this information]
```

## Example Prompts

- "What does Reddit think about Cursor IDE?"
- "Search Reddit for people complaining about Zapier pricing"
- "Reddit market research: what tools are indie hackers using for automation?"
- "Find Reddit posts comparing Claude vs GPT-4"
- "What's r/machinelearning saying about open-source LLMs?"

## Notes

- Reddit data includes post titles and body text — titles alone often reveal sentiment
- High `num_comments` posts are goldmines for qualitative research
- Free tier: 100K results/month at [xpoz.ai](https://xpoz.ai?utm_source=github&utm_medium=agent-skills&utm_campaign=reddit-research)
- For CSV export, use `export_csv()` / `exportCsv()` to download complete datasets